These models are for homicide data aggregated from 2001 - 2017
library(INLA)
Loading required package: sp
package ‘sp’ was built under R version 3.4.1Loading required package: Matrix
This is INLA_17.06.20 built 2017-06-20 03:44:36 UTC.
See www.r-inla.org/contact-us for how to get help.
library(dplyr)
package ‘dplyr’ was built under R version 3.4.4
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
library(readr)
library(stringi)
package ‘stringi’ was built under R version 3.4.4
library(rgdal)
package ‘rgdal’ was built under R version 3.4.4rgdal: version: 1.2-18, (SVN revision 718)
Geospatial Data Abstraction Library extensions to R successfully loaded
Loaded GDAL runtime: GDAL 2.1.3, released 2017/20/01
Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/3.4/Resources/library/rgdal/gdal
GDAL binary built with GEOS: FALSE
Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
Path to PROJ.4 shared files: /Library/Frameworks/R.framework/Versions/3.4/Resources/library/rgdal/proj
Linking to sp version: 1.2-7
library(spdep)
package ‘spdep’ was built under R version 3.4.4Loading required package: spData
package ‘spData’ was built under R version 3.4.4To access larger datasets in this package, install the spDataLarge package with:
`install.packages('spDataLarge', repos='https://nowosad.github.io/drat/',
type='source'))`
plot_fort_maps2 <- function(data, fill_str, legend_title, plot_title, size=0.1){
require(ggplot2)
require(ggsn)
require(broom)
ggplot() + # initialize ggplot object
geom_polygon( # make a polygon
data = data, # data frame
aes_string(x = "long", y = "lat", group = "group", # coordinates, and group them by polygons
fill = fill_str),
size=size, color="black") + # variable to use for filling
scale_fill_brewer(name=legend_title, palette = "RdYlBu", direction = -1,
drop = FALSE) + # fill with brewer colors # add title
theme(line = element_blank(),
axis.text=element_blank(), # .. tickmarks..
axis.title=element_blank(),
legend.position="none",
plot.margin = unit(c(0, 0, 0, 0), "cm"),
#legend.text=element_text(size=15),
#legend.title=element_text(size=17), # .. axis labels..
panel.background = element_blank(), plot.title = element_text(size=5)) + ggtitle(plot_title)
}
shape_to_ggplot <- function(shape){
require(broom)
gg_data <- tidy(shape)
data <- slot(shape, "data")
shape[["polyID"]] <- sapply(slot(shape, "polygons"), function(x) slot(x, "ID"))
gg_data <- merge(gg_data, shape, by.x="id", by.y="polyID")
return(gg_data)
}
SMR_data <- read_csv("~/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/CT_SMR_per_mnth_MISSING_ADJ.csv",
col_types = cols(CD_GEOCODI = col_character()))
CT_shp <- readOGR("~/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/Shapefiles/Shapefiles/CTs/", "Corrected_CTs", use_iconv = TRUE, encoding = "latin1")
OGR data source with driver: ESRI Shapefile
Source: "/Users/Sudipta/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/Shapefiles/Shapefiles/CTs", layer: "Corrected_CTs"
with 3044 features
It has 13 fields
CT_shp_gg <- shape_to_ggplot(CT_shp)
Loading required package: broom
package ‘broom’ was built under R version 3.4.4Regions defined for each Polygons
Some CTs have homicides but non pop. We have to revisit these. For now, I am turning Inf IR and SMR to zero. At most there are 2 homicides per year in these CTs. Also NaN are pop zero, hom zero. Also turning these to zero.
SMR_data <- SMR_data %>%
group_by(CD_GEOCODI) %>%
summarize(y=sum(y), E=sum(E)) %>%
mutate(SMR=y/E) %>%
mutate(SMR=replace(SMR, SMR==Inf | is.nan(SMR), 0)) %>% as.data.frame() %>% rename(obs_count=y, exp_count=E)
package ‘bindrcpp’ was built under R version 3.4.4
library(epitools)
package ‘epitools’ was built under R version 3.4.2
SMR_data$SMR_var <- SMR_data$obs_count / (SMR_data$exp_count)^2
SMR_data$CI95_lower <- NA
SMR_data$CI95_upper <- NA
SMR_data[,c("CI95_lower", "CI95_upper")] <- pois.exact(x=SMR_data$obs_count, pt=SMR_data$exp_count, conf.level=0.95)[,c(4,5)]
CT_shp@data$CD_GEOCODI <- as.character(CT_shp@data$CD_GEOCODI)
CT_shp@data <- arrange(CT_shp@data, CD_GEOCODI)
CT_wm <- poly2nb(CT_shp, snap=0.001)
nb2INLA("CT_graph.adj", CT_wm)
CT_adj <- "CT_graph.adj"
Some CTs have homicides but non pop. We have to revisit these. For now, I am turning Inf IR and SMR to zero. At most there are 2 homicides per year in these CTs. Also NaN are pop zero, hom zero. Also turning these to zero. Also turning counts to zero if underlying population is zero
BYM_data <- SMR_data %>% rename(y=obs_count, E=exp_count) %>% right_join(CT_shp@data, by="CD_GEOCODI") %>% mutate(y=replace(y, is.na(y), 0), E=replace(E, is.na(E), 0)) %>% dplyr::select(CD_GEOCODI, y, E) %>% arrange(CD_GEOCODI) %>% mutate(bymID=1:3044)
formula_poisson_null <- y ~ 1 + f(bymID, model="iid")
model_poisson_null <- inla(formula_poisson_null, family="poisson", data=BYM_data, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)
hgid: 29c6a7f1b1ff date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini] max_threads=[4]
inla_build...
number of sections=[8]
parse section=[0] name=[INLA.libR] type=[LIBR]
inla_parse_libR...
section[INLA.libR]
R_HOME=[/Library/Frameworks/R.framework/Resources]
parse section=[7] name=[INLA.Expert] type=[EXPERT]
inla_parse_expert...
section[INLA.Expert]
disable.gaussian.check=[0]
cpo.manual=[0]
jp.Rfile=[(null)]
jp.RData=NULL
jp.func=[(null)]
parse section=[1] name=[INLA.Model] type=[PROBLEM]
inla_parse_problem...
name=[INLA.Model]
openmp.strategy=[default]
store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/results.files]
output:
cpo=[0]
po=[0]
dic=[1]
kld=[1]
mlik=[1]
q=[0]
graph=[0]
gdensity=[0]
hyperparameters=[1]
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[3] name=[Predictor] type=[PREDICTOR]
inla_parse_predictor ...
section=[Predictor]
dir=[predictor]
PRIOR->name=[loggamma]
hyperid=[53001|Predictor]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 1e-05]
initialise log_precision[12]
fixed=[1]
user.scale=[1]
n=[3044]
m=[0]
ndata=[3044]
compute=[1]
read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 19/3044 (idx,y) = (19, 0)
Aext=[(null)]
AextPrecision=[1e+08]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[2] name=[INLA.Data1] type=[DATA]
inla_parse_data [section 1]...
tag=[INLA.Data1]
family=[POISSON]
likelihood=[POISSON]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f66f63d7a]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f303e4965]
read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f66f63d7a]
0/3044 (idx,a,y,d) = (0, 14.827, 12, 1)
1/3044 (idx,a,y,d) = (1, 4.88122, 4, 1)
2/3044 (idx,a,y,d) = (2, 9.75508, 31, 1)
3/3044 (idx,a,y,d) = (3, 10.764, 10, 1)
4/3044 (idx,a,y,d) = (4, 7.50958, 5, 1)
5/3044 (idx,a,y,d) = (5, 7.69529, 9, 1)
6/3044 (idx,a,y,d) = (6, 4.62971, 7, 1)
7/3044 (idx,a,y,d) = (7, 6.07998, 11, 1)
8/3044 (idx,a,y,d) = (8, 5.20853, 6, 1)
9/3044 (idx,a,y,d) = (9, 9.1703, 1, 1)
10/3044 (idx,a,y,d) = (10, 5.07622, 5, 1)
11/3044 (idx,a,y,d) = (11, 5.27241, 1, 1)
12/3044 (idx,a,y,d) = (12, 2.71774, 4, 1)
13/3044 (idx,a,y,d) = (13, 3.94485, 1, 1)
14/3044 (idx,a,y,d) = (14, 6.43779, 3, 1)
15/3044 (idx,a,y,d) = (15, 5.35615, 4, 1)
16/3044 (idx,a,y,d) = (16, 8.77675, 2, 1)
17/3044 (idx,a,y,d) = (17, 5.14462, 2, 1)
18/3044 (idx,a,y,d) = (18, 5.87517, 1, 1)
19/3044 (idx,a,y,d) = (19, 5.50689, 3, 1)
likelihood.variant=[0]
Link model [LOG]
Link order [-1]
Link variant [-1]
Link ntheta [0]
mix.use[0]
parse section=[5] name=[bymID] type=[FFIELD]
inla_parse_ffield...
section=[bymID]
dir=[random.effect00000001]
model=[iid]
PRIOR->name=[loggamma]
hyperid=[1001|bymID]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 5e-05]
correct=[-1]
constr=[0]
diagonal=[0]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 2/3044 (idx,y) = (2, 2)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 3/3044 (idx,y) = (3, 3)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 4/3044 (idx,y) = (4, 4)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 5/3044 (idx,y) = (5, 5)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 6/3044 (idx,y) = (6, 6)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 7/3044 (idx,y) = (7, 7)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 8/3044 (idx,y) = (8, 8)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 9/3044 (idx,y) = (9, 9)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 10/3044 (idx,y) = (10, 10)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 11/3044 (idx,y) = (11, 11)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 12/3044 (idx,y) = (12, 12)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 13/3044 (idx,y) = (13, 13)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 14/3044 (idx,y) = (14, 14)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 15/3044 (idx,y) = (15, 15)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 16/3044 (idx,y) = (16, 16)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 17/3044 (idx,y) = (17, 17)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 18/3044 (idx,y) = (18, 18)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 19/3044 (idx,y) = (19, 19)
file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f39c303db]
nlocations=[3044]
locations[0]=[1]
locations[1]=[2]
locations[2]=[3]
locations[3]=[4]
locations[4]=[5]
locations[5]=[6]
locations[6]=[7]
locations[7]=[8]
locations[8]=[9]
locations[9]=[10]
locations[10]=[11]
locations[11]=[12]
locations[12]=[13]
locations[13]=[14]
locations[14]=[15]
locations[15]=[16]
locations[16]=[17]
locations[17]=[18]
locations[18]=[19]
locations[19]=[20]
cyclic=[0]
initialise log_precision[4]
fixed=[0]
computed/guessed rank-deficiency = [0]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[4] name=[(Intercept)] type=[LINEAR]
inla_parse_linear...
section[(Intercept)]
dir=[fixed.effect00000001]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 0/3044 (idx,y) = (0, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 8/3044 (idx,y) = (8, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 10/3044 (idx,y) = (10, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 12/3044 (idx,y) = (12, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 14/3044 (idx,y) = (14, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 16/3044 (idx,y) = (16, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 17/3044 (idx,y) = (17, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 18/3044 (idx,y) = (18, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
Index table: number of entries[3], total length[6089]
tag start-index length
Predictor 0 3044
bymID 3044 3044
(Intercept) 6088 1
parse section=[6] name=[INLA.Parameters] type=[INLA]
inla_parse_INLA...
section[INLA.Parameters]
lincomb.derived.only = [Yes]
lincomb.derived.correlation.matrix = [No]
global_node.factor = 2.000
global_node.degree = 2147483647
reordering = -1
Contents of ai_param 0x7fe8d16059f0
Optimiser: DEFAULT METHOD
Option for domin-BFGS: epsx = 0.005
Option for domin-BFGS: epsf = 1e-05 (rounding error)
Option for domin-BFGS: epsg = 0.005
Option for GSL-BFGS2: tol = 0.1
Option for GSL-BFGS2: step_size = 1
Option for GSL-BFGS2: epsx = 0.005
Option for GSL-BFGS2: epsf = 0.000353553
Option for GSL-BFGS2: epsg = 0.005
Restart: 0
Mode known: No
Gaussian approximation:
abserr_func = 0.0005
abserr_step = 0.0005
optpar_fp = 0
optpar_nr_step_factor = -0.1
Gaussian data: No
Strategy: Use a mean-skew corrected Gaussian by fitting a Skew-Normal
Fast mode: On
Use linear approximation to log(|Q +c|)? Yes
Method: Compute the derivative exact
Parameters for improved approximations
Number of points evaluate: 9
Step length to compute derivatives numerically: 0.000100002
Stencil to compute derivatives numerically: 5
Cutoff value to construct local neigborhood: 0.0001
Log calculations: On
Log calculated marginal for the hyperparameters: On
Integration strategy: Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
f0 (CCD only): 1.100000
dz (GRID only): 0.750000
Adjust weights (GRID only): On
Difference in log-density limit (GRID only): 6.000000
Skip configurations with (presumed) small density (GRID only): On
Gradient is computed using Central difference with step-length 0.010000
Hessian is computed using Central difference with step-length 0.100000
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Perform a Monte Carlo error-test? [No]
Interpolator [Auto]
CPO required diff in log-density [3]
Stupid search mode:
Status [On]
Max iter [1000]
Factor [1.05]
Numerical integration of hyperparameters:
Maximum number of function evaluations [100000]
Relative error ....................... [1e-05]
Absolute error ....................... [1e-06]
To stabilise the numerical optimisation:
Minimum value of the -Hessian [-inf]
CPO manual calculation[No]
Laplace-correction is Disabled.
inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini]
inla_INLA...
Strategy = [DEFAULT]
Size is [6089]
Chose OpenMP-strategy [LARGE]
Chose density-strategy [HIGH]
Size of graph=[6089] constraints=[0]
Found optimal reordering=[amdc] nnz(L)=[15221] and use_global_nodes(user)=[no]
List of hyperparameters:
theta[0] = [Log precision for bymID]
Optimise using DEFAULT METHOD
max.logdens= -12594.216580 fn= 1 theta= 3.990000 range=[-0.188 2.852]
max.logdens= -10970.805657 fn= 3 theta= 3.000000 range=[-0.415 3.617]
max.logdens= -10953.743044 fn= 4 theta= 2.990000 range=[-0.418 3.622]
max.logdens= -8451.523025 fn= 6 theta= 0.829830 range=[-1.422 5.356]
max.logdens= -8447.884013 fn= 7 theta= 0.819830 range=[-1.428 5.359]
max.logdens= -8364.982909 fn= 10 theta= 0.263314 range=[-1.771 5.501]
max.logdens= -8364.478189 fn= 11 theta= 0.273314 range=[-1.765 5.499]
Iter=1 |grad|=53.3 |x-x.old|=3.74 |f-f.old|=4.24e+03
max.logdens= -8363.167032 fn= 14 theta= 0.334507 range=[-1.726 5.486]
max.logdens= -8363.015325 fn= 15 theta= 0.324507 range=[-1.732 5.488]
max.logdens= -8362.943552 fn= 16 theta= 0.344507 range=[-1.719 5.483]
Iter=2 |grad|=3.59 |x-x.old|=0.0712 |f-f.old|=1.82
Iter=3 |grad|=0.069 |x-x.old|=0.00498(pass) |f-f.old|=0.198
Number of function evaluations = 21
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]
717.946269
Eigenvectors of the Hessian
1.000000
Eigenvalues of the Hessian
717.946269
StDev/Correlation matrix (scaled inverse Hessian)
0.037321
Compute corrected stdev for theta[0]: negative 0.986960 positive 0.996278
max.logdens= -8362.935007 fn= 27 theta= 0.339488 range=[-1.723 5.484]
max.logdens= -8362.933247 fn= 28 theta= 0.339488 range=[-1.723 5.484]
config 0=[ 0.00] log(rel.dens)= 0.00, [3] accept, compute, 2.17s
config 1=[ 0.75] log(rel.dens)=-0.46, [1] accept, compute, 2.29s
config 2=[ -0.75] log(rel.dens)=-0.29, [2] accept, compute, 2.32s
config 3=[ 1.50] log(rel.dens)=-1.11, [0] accept, compute, 2.34s
config 4=[ -1.50] log(rel.dens)=-1.16, [3] accept, compute, 2.37s
config 5=[ 3.00] log(rel.dens)=-4.52, [0] accept, compute, 2.31s
config 6=[ 2.25] log(rel.dens)=-2.56, [1] accept, compute, 2.39s
config 7=[ -2.25] log(rel.dens)=-2.53, [2] accept, compute, 2.36s
config 8=[ 3.75] log(rel.dens)=-7.02, reject, 0.06s
config 9=[ -4.50] log(rel.dens)=-9.95, reject, 0.06s
config 10=[ -3.75] log(rel.dens)=-6.84, reject, 0.09s
config 11=[ -5.25] log(rel.dens)=-13.33, reject, 0.08s
config 12=[ -3.00] log(rel.dens)=-4.45, [3] accept, compute, 1.24s
Combine the densities with relative weights:
config 0/ 9=[ 0.00] weight = 1.000 adjusted weight = 0.977 neff = 2174.87
config 1/ 9=[ 0.75] weight = 0.632 adjusted weight = 0.625 neff = 2162.28
config 2/ 9=[ -0.75] weight = 0.747 adjusted weight = 0.739 neff = 2187.46
config 3/ 9=[ 1.50] weight = 0.328 adjusted weight = 0.337 neff = 2149.27
config 4/ 9=[ -1.50] weight = 0.313 adjusted weight = 0.322 neff = 2199.94
config 5/ 9=[ 3.00] weight = 0.011 adjusted weight = 0.013 neff = 2123.14
config 6/ 9=[ 2.25] weight = 0.077 adjusted weight = 0.085 neff = 2136.29
config 7/ 9=[ -2.25] weight = 0.079 adjusted weight = 0.087 neff = 2212.23
config 8/ 9=[ -3.00] weight = 0.012 adjusted weight = 0.014 neff = 2224.39
Done.
Expected effective number of parameters: 2175.145(17.278), eqv.#replicates: 1.399
DIC:
Mean of Deviance................. 12419.3
Deviance at Mean................. 10279.8
Effective number of parameters... 2139.48
DIC.............................. 14558.7
Marginal likelihood: Integration -8365.348296 Gaussian-approx -8365.304266
Compute the marginal for each of the 1 hyperparameters
Interpolation method: Auto
Compute the marginal for theta[0] to theta[0] using numerical integration...
Compute the marginal for theta[0] to theta[0] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/results.files]
Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini]
Preparations : 0.062 seconds
Approx inference: 7.699 seconds [3.0|0.0|15.0|75.3|6.7]%
Output : 0.499 seconds
---------------------------------
Total : 8.261 seconds
Plot smoothed and unsmoothed rates
breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
CT_shp_gg_SMR <- CT_shp_gg[,-1] %>% left_join(SMR_data[,c(1,4)], by="CD_GEOCODI") %>% mutate(cut=cut(SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))
Column `CD_GEOCODI` joining factor and character vector, coercing into character vector
plot_fort_maps2(CT_shp_gg_SMR, "cut","Unsmoothed SMR", "Aggregate SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")
library(RColorBrewer)
set.seed(2014)
plot(1,1, type="n", xlim=c(500,650), ylim=c(0,10),
main= "Confidence intervals of the SMR",
xlab="County", ylab="Relative Risk", xaxt="n")
abline(h=1, lty=2)
for(i in 500:650){
if(!is.na(SMR_data$exp_count[i])){
if(SMR_data$CI95_lower[i]>1 ) {
sig.col <- brewer.pal(4, "Reds")[4]
col <- sig.col
lty <- 2
#text(i, SMR_data$CI95_upper[i]+.31,
#srt=90, col=sig.col, cex=.85)
} else {
col <- "black"
lty <- 1
}
lines(c(i,i), c(SMR_data$CI95_lower[i],SMR_data$CI95_upper[i]), col=col, lty=lty)
points(x=i, y=SMR_data$SMR_17yr[i], pch=18, col=col)
}
}
breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
results <- data.frame(bymID=BYM_data$bymID, CD_GEOCODI=BYM_data$CD_GEOCODI, fit_SMR = model_poisson_null$summary.fitted.values$mean)
CT_shp_gg_SMR_smth <- CT_shp_gg_SMR %>% left_join(results, by="CD_GEOCODI") %>% mutate(fit_cut=cut(fit_SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))
Column `CD_GEOCODI` joining character vector and factor, coercing into character vector
plot_fort_maps2(CT_shp_gg_SMR_smth, "fit_cut","Fitted SMR", "Aggregate Poisson smoothed SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")
formula_bym_null <- y ~ f(bymID, model="bym", graph=CT_adj)
model_bym_null <- inla(formula_bym_null, family="poisson", data=BYM_data, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)
hgid: 29c6a7f1b1ff date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini] max_threads=[4]
inla_build...
number of sections=[8]
parse section=[0] name=[INLA.libR] type=[LIBR]
inla_parse_libR...
section[INLA.libR]
R_HOME=[/Library/Frameworks/R.framework/Resources]
parse section=[7] name=[INLA.Expert] type=[EXPERT]
inla_parse_expert...
section[INLA.Expert]
disable.gaussian.check=[0]
cpo.manual=[0]
jp.Rfile=[(null)]
jp.RData=NULL
jp.func=[(null)]
parse section=[1] name=[INLA.Model] type=[PROBLEM]
inla_parse_problem...
name=[INLA.Model]
openmp.strategy=[default]
store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/results.files]
output:
cpo=[0]
po=[0]
dic=[1]
kld=[1]
mlik=[1]
q=[0]
graph=[0]
gdensity=[0]
hyperparameters=[1]
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[3] name=[Predictor] type=[PREDICTOR]
inla_parse_predictor ...
section=[Predictor]
dir=[predictor]
PRIOR->name=[loggamma]
hyperid=[53001|Predictor]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 1e-05]
initialise log_precision[12]
fixed=[1]
user.scale=[1]
n=[3044]
m=[0]
ndata=[3044]
compute=[1]
read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 19/3044 (idx,y) = (19, 0)
Aext=[(null)]
AextPrecision=[1e+08]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[2] name=[INLA.Data1] type=[DATA]
inla_parse_data [section 1]...
tag=[INLA.Data1]
family=[POISSON]
likelihood=[POISSON]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f1081f6ee]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f447a8bb9]
read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f1081f6ee]
0/3044 (idx,a,y,d) = (0, 14.827, 12, 1)
1/3044 (idx,a,y,d) = (1, 4.88122, 4, 1)
2/3044 (idx,a,y,d) = (2, 9.75508, 31, 1)
3/3044 (idx,a,y,d) = (3, 10.764, 10, 1)
4/3044 (idx,a,y,d) = (4, 7.50958, 5, 1)
5/3044 (idx,a,y,d) = (5, 7.69529, 9, 1)
6/3044 (idx,a,y,d) = (6, 4.62971, 7, 1)
7/3044 (idx,a,y,d) = (7, 6.07998, 11, 1)
8/3044 (idx,a,y,d) = (8, 5.20853, 6, 1)
9/3044 (idx,a,y,d) = (9, 9.1703, 1, 1)
10/3044 (idx,a,y,d) = (10, 5.07622, 5, 1)
11/3044 (idx,a,y,d) = (11, 5.27241, 1, 1)
12/3044 (idx,a,y,d) = (12, 2.71774, 4, 1)
13/3044 (idx,a,y,d) = (13, 3.94485, 1, 1)
14/3044 (idx,a,y,d) = (14, 6.43779, 3, 1)
15/3044 (idx,a,y,d) = (15, 5.35615, 4, 1)
16/3044 (idx,a,y,d) = (16, 8.77675, 2, 1)
17/3044 (idx,a,y,d) = (17, 5.14462, 2, 1)
18/3044 (idx,a,y,d) = (18, 5.87517, 1, 1)
19/3044 (idx,a,y,d) = (19, 5.50689, 3, 1)
likelihood.variant=[0]
Link model [LOG]
Link order [-1]
Link variant [-1]
Link ntheta [0]
mix.use[0]
parse section=[5] name=[bymID] type=[FFIELD]
inla_parse_ffield...
section=[bymID]
dir=[random.effect00000001]
model=[bym]
PRIOR0->name=[loggamma]
hyperid=[10001|bymID]
PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR0->PARAMETERS0=[1, 0.0005]
PRIOR1->name=[loggamma]
hyperid=[10002|bymID]
PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR1->PARAMETERS1=[1, 0.0005]
correct=[-1]
constr=[0]
diagonal=[1.01511e-05]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 2/3044 (idx,y) = (2, 2)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 3/3044 (idx,y) = (3, 3)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 4/3044 (idx,y) = (4, 4)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 5/3044 (idx,y) = (5, 5)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 6/3044 (idx,y) = (6, 6)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 7/3044 (idx,y) = (7, 7)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 8/3044 (idx,y) = (8, 8)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 9/3044 (idx,y) = (9, 9)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 10/3044 (idx,y) = (10, 10)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 11/3044 (idx,y) = (11, 11)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 12/3044 (idx,y) = (12, 12)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 13/3044 (idx,y) = (13, 13)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 14/3044 (idx,y) = (14, 14)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 15/3044 (idx,y) = (15, 15)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 16/3044 (idx,y) = (16, 16)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 17/3044 (idx,y) = (17, 17)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 18/3044 (idx,y) = (18, 18)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 19/3044 (idx,y) = (19, 19)
read graph from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f117a0105]
file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f56bde848]
nlocations=[3044]
locations[0]=[1]
locations[1]=[2]
locations[2]=[3]
locations[3]=[4]
locations[4]=[5]
locations[5]=[6]
locations[6]=[7]
locations[7]=[8]
locations[8]=[9]
locations[9]=[10]
locations[10]=[11]
locations[11]=[12]
locations[12]=[13]
locations[13]=[14]
locations[14]=[15]
locations[15]=[16]
locations[16]=[17]
locations[17]=[18]
locations[18]=[19]
locations[19]=[20]
initialise log_precision (iid component)[4]
fixed=[0]
initialise log_precision (spatial component)[4]
fixed=[0]
adjust.for.con.comp[1]
scale.model[0]
read extra constraint from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6c0d2be2]
Constraint[0]
A[3044] = 1.000000
A[3045] = 1.000000
A[3046] = 1.000000
A[3047] = 1.000000
A[3048] = 1.000000
A[3049] = 1.000000
A[3050] = 1.000000
A[3051] = 1.000000
A[3052] = 1.000000
A[3053] = 1.000000
A[3054] = 1.000000
A[3055] = 1.000000
A[3056] = 1.000000
A[3057] = 1.000000
A[3058] = 1.000000
A[3059] = 1.000000
A[3060] = 1.000000
A[3061] = 1.000000
A[3062] = 1.000000
A[3063] = 1.000000
A[3064] = 1.000000
e[0] = 0.000000
rank-deficiency is *defined* [1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[4] name=[(Intercept)] type=[LINEAR]
inla_parse_linear...
section[(Intercept)]
dir=[fixed.effect00000001]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 0/3044 (idx,y) = (0, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 8/3044 (idx,y) = (8, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 10/3044 (idx,y) = (10, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 12/3044 (idx,y) = (12, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 14/3044 (idx,y) = (14, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 16/3044 (idx,y) = (16, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 17/3044 (idx,y) = (17, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 18/3044 (idx,y) = (18, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
Index table: number of entries[3], total length[9133]
tag start-index length
Predictor 0 3044
bymID 3044 6088
(Intercept) 9132 1
parse section=[6] name=[INLA.Parameters] type=[INLA]
inla_parse_INLA...
section[INLA.Parameters]
lincomb.derived.only = [Yes]
lincomb.derived.correlation.matrix = [No]
global_node.factor = 2.000
global_node.degree = 2147483647
reordering = -1
Contents of ai_param 0x7fe401701710
Optimiser: DEFAULT METHOD
Option for domin-BFGS: epsx = 0.005
Option for domin-BFGS: epsf = 1e-05 (rounding error)
Option for domin-BFGS: epsg = 0.005
Option for GSL-BFGS2: tol = 0.1
Option for GSL-BFGS2: step_size = 1
Option for GSL-BFGS2: epsx = 0.005
Option for GSL-BFGS2: epsf = 0.000353553
Option for GSL-BFGS2: epsg = 0.005
Restart: 0
Mode known: No
Gaussian approximation:
abserr_func = 0.0005
abserr_step = 0.0005
optpar_fp = 0
optpar_nr_step_factor = -0.1
Gaussian data: No
Strategy: Use a mean-skew corrected Gaussian by fitting a Skew-Normal
Fast mode: On
Use linear approximation to log(|Q +c|)? Yes
Method: Compute the derivative exact
Parameters for improved approximations
Number of points evaluate: 9
Step length to compute derivatives numerically: 0.000100002
Stencil to compute derivatives numerically: 5
Cutoff value to construct local neigborhood: 0.0001
Log calculations: On
Log calculated marginal for the hyperparameters: On
Integration strategy: Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
f0 (CCD only): 1.100000
dz (GRID only): 0.750000
Adjust weights (GRID only): On
Difference in log-density limit (GRID only): 6.000000
Skip configurations with (presumed) small density (GRID only): On
Gradient is computed using Central difference with step-length 0.010000
Hessian is computed using Central difference with step-length 0.100000
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Perform a Monte Carlo error-test? [No]
Interpolator [Auto]
CPO required diff in log-density [3]
Stupid search mode:
Status [On]
Max iter [1000]
Factor [1.05]
Numerical integration of hyperparameters:
Maximum number of function evaluations [100000]
Relative error ....................... [1e-05]
Absolute error ....................... [1e-06]
To stabilise the numerical optimisation:
Minimum value of the -Hessian [-inf]
CPO manual calculation[No]
Laplace-correction is Disabled.
inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini]
inla_INLA...
Strategy = [DEFAULT]
Size is [9133]
Chose OpenMP-strategy [LARGE]
Chose density-strategy [HIGH]
Size of graph=[9133] constraints=[1]
Found optimal reordering=[amdbarc] nnz(L)=[67024] and use_global_nodes(user)=[no]
List of hyperparameters:
theta[0] = [Log precision for bymID (idd component)]
theta[1] = [Log precision for bymID (spatial component)]
Optimise using DEFAULT METHOD
max.logdens= -12212.491312 fn= 1 theta= 4.000000 3.990000 range=[-0.645 3.122]
max.logdens= -12203.547336 fn= 2 theta= 3.990000 4.000000 range=[-0.643 3.128]
max.logdens= -10786.982766 fn= 5 theta= 3.038828 3.724049 range=[-0.805 3.689]
max.logdens= -10784.450551 fn= 6 theta= 3.038828 3.714049 range=[-0.807 3.690]
max.logdens= -10772.356266 fn= 7 theta= 3.028828 3.724049 range=[-0.806 3.693]
max.logdens= -8508.443163 fn= 10 theta= 0.772859 3.073493 range=[-1.574 5.398]
max.logdens= -8507.873932 fn= 11 theta= 0.772859 3.063493 range=[-1.574 5.398]
max.logdens= -8506.273411 fn= 12 theta= 0.762859 3.073493 range=[-1.579 5.400]
max.logdens= -8470.898848 fn= 16 theta= 0.375390 2.959380 range=[-1.808 5.497]
max.logdens= -8470.471804 fn= 17 theta= 0.375390 2.949380 range=[-1.808 5.497]
max.logdens= -8470.367384 fn= 19 theta= 0.385390 2.959380 range=[-1.802 5.494]
Iter=1 |grad|=68.7 |x-x.old|=2.67 |f-f.old|=3.75e+03
max.logdens= -8427.186006 fn= 21 theta= 0.614126 1.988296 range=[-1.790 5.459]
max.logdens= -8426.615755 fn= 22 theta= 0.604126 1.988296 range=[-1.794 5.461]
max.logdens= -8390.057305 fn= 26 theta= 1.001508 0.412576 range=[-2.029 5.430]
max.logdens= -8389.522477 fn= 27 theta= 1.001508 0.402576 range=[-2.032 5.431]
max.logdens= -8388.645792 fn= 28 theta= 0.991508 0.412576 range=[-2.031 5.432]
max.logdens= -8378.915904 fn= 32 theta= 1.175830 -0.296499 range=[-2.203 5.456]
max.logdens= -8378.544737 fn= 33 theta= 1.175830 -0.306499 range=[-2.206 5.457]
max.logdens= -8377.939108 fn= 34 theta= 1.165830 -0.296499 range=[-2.204 5.457]
max.logdens= -8377.900684 fn= 38 theta= 1.210701 -0.438341 range=[-2.242 5.465]
max.logdens= -8377.677702 fn= 39 theta= 1.210701 -0.448341 range=[-2.245 5.466]
max.logdens= -8377.125364 fn= 40 theta= 1.200701 -0.438341 range=[-2.244 5.467]
Iter=2 |grad|=82 |x-x.old|=2.47 |f-f.old|=93
max.logdens= -8374.927208 fn= 44 theta= 1.189882 -0.590640 range=[-2.298 5.485]
max.logdens= -8374.443531 fn= 45 theta= 1.179882 -0.590640 range=[-2.299 5.486]
Iter=3 |grad|=40.5 |x-x.old|=0.139 |f-f.old|=3.02
max.logdens= -8369.345232 fn= 54 theta= 1.063970 -0.482892 range=[-2.281 5.491]
max.logdens= -8369.007640 fn= 56 theta= 1.053970 -0.482892 range=[-2.283 5.493]
max.logdens= -8364.286630 fn= 59 theta= 0.738943 -0.078104 range=[-2.227 5.511]
max.logdens= -8364.072185 fn= 60 theta= 0.738943 -0.088104 range=[-2.230 5.512]
max.logdens= -8363.728975 fn= 62 theta= 0.748943 -0.078104 range=[-2.225 5.510]
max.logdens= -8363.362484 fn= 64 theta= 0.815243 -0.173128 range=[-2.236 5.505]
max.logdens= -8363.279466 fn= 67 theta= 0.825243 -0.173128 range=[-2.234 5.503]
max.logdens= -8363.272041 fn= 68 theta= 0.815243 -0.163128 range=[-2.234 5.504]
Iter=4 |grad|=11.1 |x-x.old|=0.417 |f-f.old|=11.5
max.logdens= -8363.054352 fn= 70 theta= 0.818023 -0.061950 range=[-2.204 5.497]
max.logdens= -8363.016470 fn= 71 theta= 0.808023 -0.061950 range=[-2.206 5.499]
Iter=5 |grad|=2.59 |x-x.old|=0.0614 |f-f.old|=0.338
max.logdens= -8363.011411 fn= 81 theta= 0.803432 -0.066380 range=[-2.209 5.500]
max.logdens= -8363.009833 fn= 86 theta= 0.806535 -0.070820 range=[-2.209 5.499]
Iter=6 |grad|=0.118 |x-x.old|=0.0134 |f-f.old|=0.0144
max.logdens= -8363.003242 fn= 94 theta= 0.806535 -0.071119 range=[-2.209 5.499]
Iter=7 |grad|=0.0979 |x-x.old|=0.000212(pass) |f-f.old|=0.000194(pass) Reached numerical limit!
Number of function evaluations = 107
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]
405.843789 110.027626
110.027626 73.194881
Eigenvectors of the Hessian
0.957608 -0.288076
0.288076 0.957608
Eigenvalues of the Hessian
438.943261
40.095408
StDev/Correlation matrix (scaled inverse Hessian)
0.064489 -0.638384
0.151855
Compute corrected stdev for theta[0]: negative 0.978417 positive 0.984646
Compute corrected stdev for theta[1]: negative 0.911574 positive 0.962673
max.logdens= -8363.009798 fn= 121 theta= 0.806535 -0.071119 range=[-2.209 5.499]
config 0=[ -0.75 0.00] log(rel.dens)=-0.35, [1] accept, compute, 10.34s
config 1=[ 0.00 0.00] log(rel.dens)=-0.07, [3] accept, compute, 10.68s
config 2=[ 0.00 -0.75] log(rel.dens)=-0.38, [2] accept, compute, 10.71s
config 3=[ 0.75 0.00] log(rel.dens)=-0.31, [0] accept, compute, 10.92s
config 4=[ -0.75 0.75] log(rel.dens)=-0.63, [3] accept, compute, 10.26s
config 5=[ 0.00 0.75] log(rel.dens)=-0.33, [1] accept, compute, 10.75s
config 6=[ -0.75 -0.75] log(rel.dens)=-0.64, [2] accept, compute, 10.84s
config 7=[ 0.75 -0.75] log(rel.dens)=-0.53, [0] accept, compute, 10.74s
config 8=[ 0.75 0.75] log(rel.dens)=-0.64, [3] accept, compute, 11.07s
config 9=[ 0.00 -1.50] log(rel.dens)=-1.36, [1] accept, compute, 11.10s
config 10=[ -1.50 0.00] log(rel.dens)=-1.14, [2] accept, compute, 11.08s
config 11=[ 1.50 0.00] log(rel.dens)=-1.15, [0] accept, compute, 11.07s
config 12=[ -0.75 1.50] log(rel.dens)=-1.72, [1] accept, compute, 11.30s
config 13=[ 0.75 -1.50] log(rel.dens)=-1.46, [2] accept, compute, 11.45s
config 14=[ 0.00 1.50] log(rel.dens)=-1.22, [3] accept, compute, 12.14s
config 15=[ -0.75 -1.50] log(rel.dens)=-1.88, [0] accept, compute, 12.03s
config 16=[ 0.75 1.50] log(rel.dens)=-1.47, [1] accept, compute, 13.76s
config 17=[ -1.50 -0.75] log(rel.dens)=-1.57, [2] accept, compute, 13.62s
config 18=[ 1.50 -0.75] log(rel.dens)=-1.38, [3] accept, compute, 13.52s
config 19=[ -1.50 0.75] log(rel.dens)=-1.57, [0] accept, compute, 14.18s
config 20=[ 1.50 0.75] log(rel.dens)=-1.48, [1] accept, compute, 16.25s
config 21=[ -1.50 -1.50] log(rel.dens)=-2.64, [2] accept, compute, 16.38s
config 22=[ 1.50 1.50] log(rel.dens)=-2.33, [3] accept, compute, 16.38s
config 23=[ 1.50 -1.50] log(rel.dens)=-2.16, [0] accept, compute, 15.73s
config 24=[ -1.50 1.50] log(rel.dens)=-2.77, [1] accept, compute, 12.06s
config 25=[ 2.25 0.00] log(rel.dens)=-2.56, [3] accept, compute, 11.70s
config 26=[ 0.00 -2.25] log(rel.dens)=-3.02, [2] accept, compute, 11.90s
config 27=[ -2.25 0.00] log(rel.dens)=-2.79, [0] accept, compute, 11.84s
config 28=[ 0.00 2.25] log(rel.dens)=-2.70, [1] accept, compute, 10.91s
config 29=[ -0.75 -2.25] log(rel.dens)=-3.58, [2] accept, compute, 10.83s
config 30=[ 2.25 0.75] log(rel.dens)=-2.91, [3] accept, compute, 11.25s
config 31=[ 0.75 -2.25] log(rel.dens)=-3.06, [0] accept, compute, 10.58s
config 32=[ -2.25 0.75] log(rel.dens)=-3.20, [0] accept, compute, 11.06s
config 33=[ 2.25 -0.75] log(rel.dens)=-2.55, [2] accept, compute, 11.37s
config 34=[ -2.25 -0.75] log(rel.dens)=-2.88, [1] accept, compute, 11.68s
config 35=[ -0.75 2.25] log(rel.dens)=-3.41, [3] accept, compute, 11.40s
config 36=[ -2.25 -1.50] log(rel.dens)=-4.09, [2] accept, compute, 10.97s
config 37=[ 0.75 2.25] log(rel.dens)=-2.97, [0] accept, compute, 11.18s
config 38=[ 2.25 -1.50] log(rel.dens)=-3.41, [1] accept, compute, 11.36s
config 39=[ -1.50 -2.25] log(rel.dens)=-4.65, [3] accept, compute, 11.43s
config 40=[ 2.25 1.50] log(rel.dens)=-3.68, [2] accept, compute, 10.56s
config 41=[ -1.50 2.25] log(rel.dens)=-4.42, [0] accept, compute, 10.65s
config 42=[ 1.50 -2.25] log(rel.dens)=-3.31, [1] accept, compute, 10.45s
config 43=[ -2.25 1.50] log(rel.dens)=-4.15, [3] accept, compute, 10.21s
config 44=[ 1.50 2.25] log(rel.dens)=-3.50, [2] accept, compute, 11.32s
config 45=[ 0.00 3.00] log(rel.dens)=-4.70, [0] accept, compute, 11.10s
config 46=[ -0.75 -3.00] log(rel.dens)=-6.36, reject, 0.25s
config 47=[ 3.00 0.00] log(rel.dens)=-4.46, [1] accept, compute, 11.55s
config 48=[ 0.00 -3.00] log(rel.dens)=-5.55, [3] accept, compute, 11.53s
config 49=[ -3.00 0.00] log(rel.dens)=-4.50, [2] accept, compute, 11.92s
config 50=[ -3.00 0.75] log(rel.dens)=-5.02, [0] accept, compute, 11.72s
config 51=[ 3.00 0.75] log(rel.dens)=-4.93, [1] accept, compute, 11.50s
config 52=[ -0.75 3.00] log(rel.dens)=-5.35, [3] accept, compute, 11.73s
config 53=[ 0.75 -3.00] log(rel.dens)=-5.46, [2] accept, compute, 11.45s
config 54=[ 3.00 -0.75] log(rel.dens)=-4.40, [1] accept, compute, 11.38s
config 55=[ 0.75 3.00] log(rel.dens)=-4.58, [0] accept, compute, 11.52s
config 56=[ -3.00 -0.75] log(rel.dens)=-4.83, [3] accept, compute, 11.43s
config 57=[ -2.25 -2.25] log(rel.dens)=-6.21, reject, 0.34s
config 58=[ -2.25 2.25] log(rel.dens)=-6.20, reject, 0.26s
config 59=[ -1.50 3.00] log(rel.dens)=-6.70, reject, 0.29s
config 60=[ -3.00 -1.50] log(rel.dens)=-6.06, reject, 0.32s
config 61=[ 2.25 2.25] log(rel.dens)=-4.83, [2] accept, compute, 11.28s
config 62=[ 2.25 -2.25] log(rel.dens)=-4.22, [1] accept, compute, 11.69s
config 63=[ -3.00 1.50] log(rel.dens)=-6.34, reject, 0.28s
config 64=[ 1.50 -3.00] log(rel.dens)=-5.31, [0] accept, compute, 11.60s
config 65=[ 3.00 1.50] log(rel.dens)=-5.71, [3] accept, compute, 11.76s
config 66=[ 0.00 -3.75] log(rel.dens)=-9.10, reject, 0.33s
config 67=[ 1.50 3.00] log(rel.dens)=-5.18, [2] accept, compute, 11.66s
config 68=[ 3.00 2.25] log(rel.dens)=-6.87, reject, 0.26s
config 69=[ 2.25 3.00] log(rel.dens)=-6.40, reject, 0.20s
config 70=[ 2.25 -3.00] log(rel.dens)=-5.88, [0] accept, compute, 11.20s
config 71=[ 0.00 3.75] log(rel.dens)=-7.36, reject, 0.22s
config 72=[ 3.75 0.00] log(rel.dens)=-6.96, reject, 0.27s
config 73=[ 3.00 -1.50] log(rel.dens)=-4.67, [1] accept, compute, 11.92s
config 74=[ -3.75 0.00] log(rel.dens)=-7.03, reject, 0.28s
config 75=[ -3.75 -0.75] log(rel.dens)=-7.32, reject, 0.20s
config 76=[ 3.00 -3.00] log(rel.dens)=-6.94, reject, 0.13s
config 77=[ 3.00 -2.25] log(rel.dens)=-5.47, [3] accept, compute, 11.25s
Combine the densities with relative weights:
config 0/64=[ -0.75 0.00] weight = 0.756 adjusted weight = 0.733 neff = 2084.27
config 1/64=[ 0.00 0.00] weight = 1.000 adjusted weight = 0.957 neff = 2070.66
config 2/64=[ 0.00 -0.75] weight = 0.735 adjusted weight = 0.712 neff = 2072.02
config 3/64=[ 0.75 0.00] weight = 0.787 adjusted weight = 0.763 neff = 2056.92
config 4/64=[ -0.75 0.75] weight = 0.574 adjusted weight = 0.564 neff = 2084.89
config 5/64=[ 0.00 0.75] weight = 0.772 adjusted weight = 0.748 neff = 2071.00
config 6/64=[ -0.75 -0.75] weight = 0.570 adjusted weight = 0.559 neff = 2085.26
config 7/64=[ 0.75 -0.75] weight = 0.634 adjusted weight = 0.623 neff = 2058.59
config 8/64=[ 0.75 0.75] weight = 0.567 adjusted weight = 0.557 neff = 2057.03
config 9/64=[ 0.00 -1.50] weight = 0.277 adjusted weight = 0.279 neff = 2075.26
config 10/64=[ -1.50 0.00] weight = 0.344 adjusted weight = 0.347 neff = 2097.74
config 11/64=[ 1.50 0.00] weight = 0.342 adjusted weight = 0.345 neff = 2043.15
config 12/64=[ -0.75 1.50] weight = 0.193 adjusted weight = 0.197 neff = 2087.27
config 13/64=[ 0.75 -1.50] weight = 0.249 adjusted weight = 0.254 neff = 2062.25
config 14/64=[ 0.00 1.50] weight = 0.318 adjusted weight = 0.320 neff = 2073.02
config 15/64=[ -0.75 -1.50] weight = 0.164 adjusted weight = 0.167 neff = 2088.29
config 16/64=[ 0.75 1.50] weight = 0.247 adjusted weight = 0.252 neff = 2058.81
config 17/64=[ -1.50 -0.75] weight = 0.224 adjusted weight = 0.228 neff = 2098.54
config 18/64=[ 1.50 -0.75] weight = 0.272 adjusted weight = 0.277 neff = 2045.23
config 19/64=[ -1.50 0.75] weight = 0.223 adjusted weight = 0.227 neff = 2098.74
config 20/64=[ 1.50 0.75] weight = 0.246 adjusted weight = 0.251 neff = 2042.94
config 21/64=[ -1.50 -1.50] weight = 0.077 adjusted weight = 0.081 neff = 2101.02
config 22/64=[ 1.50 1.50] weight = 0.105 adjusted weight = 0.111 neff = 2044.52
config 23/64=[ 1.50 -1.50] weight = 0.124 adjusted weight = 0.132 neff = 2049.25
config 24/64=[ -1.50 1.50] weight = 0.067 adjusted weight = 0.071 neff = 2101.34
config 25/64=[ 2.25 0.00] weight = 0.084 adjusted weight = 0.090 neff = 2029.31
config 26/64=[ 0.00 -2.25] weight = 0.052 adjusted weight = 0.056 neff = 2080.39
config 27/64=[ -2.25 0.00] weight = 0.066 adjusted weight = 0.071 neff = 2111.36
config 28/64=[ 0.00 2.25] weight = 0.072 adjusted weight = 0.077 neff = 2076.60
config 29/64=[ -0.75 -2.25] weight = 0.030 adjusted weight = 0.032 neff = 2092.93
config 30/64=[ 2.25 0.75] weight = 0.059 adjusted weight = 0.064 neff = 2028.78
config 31/64=[ 0.75 -2.25] weight = 0.050 adjusted weight = 0.055 neff = 2067.88
config 32/64=[ -2.25 0.75] weight = 0.044 adjusted weight = 0.048 neff = 2112.55
config 33/64=[ 2.25 -0.75] weight = 0.084 adjusted weight = 0.091 neff = 2031.64
config 34/64=[ -2.25 -0.75] weight = 0.060 adjusted weight = 0.065 neff = 2111.62
config 35/64=[ -0.75 2.25] weight = 0.036 adjusted weight = 0.039 neff = 2091.08
config 36/64=[ -2.25 -1.50] weight = 0.018 adjusted weight = 0.020 neff = 2113.82
config 37/64=[ 0.75 2.25] weight = 0.055 adjusted weight = 0.060 neff = 2062.29
config 38/64=[ 2.25 -1.50] weight = 0.035 adjusted weight = 0.040 neff = 2036.24
config 39/64=[ -1.50 -2.25] weight = 0.010 adjusted weight = 0.012 neff = 2105.43
config 40/64=[ 2.25 1.50] weight = 0.027 adjusted weight = 0.031 neff = 2030.01
config 41/64=[ -1.50 2.25] weight = 0.013 adjusted weight = 0.015 neff = 2105.22
config 42/64=[ 1.50 -2.25] weight = 0.039 adjusted weight = 0.044 neff = 2055.10
config 43/64=[ -2.25 1.50] weight = 0.017 adjusted weight = 0.019 neff = 2115.10
config 44/64=[ 1.50 2.25] weight = 0.032 adjusted weight = 0.036 neff = 2047.56
config 45/64=[ 0.00 3.00] weight = 0.010 adjusted weight = 0.011 neff = 2081.53
config 46/64=[ 3.00 0.00] weight = 0.012 adjusted weight = 0.014 neff = 2015.35
config 47/64=[ 0.00 -3.00] weight = 0.004 adjusted weight = 0.005 neff = 2087.57
config 48/64=[ -3.00 0.00] weight = 0.012 adjusted weight = 0.014 neff = 2124.52
config 49/64=[ -3.00 0.75] weight = 0.007 adjusted weight = 0.008 neff = 2125.97
config 50/64=[ 3.00 0.75] weight = 0.008 adjusted weight = 0.009 neff = 2014.54
config 51/64=[ -0.75 3.00] weight = 0.005 adjusted weight = 0.006 neff = 2096.00
config 52/64=[ 0.75 -3.00] weight = 0.005 adjusted weight = 0.005 neff = 2075.58
config 53/64=[ 3.00 -0.75] weight = 0.013 adjusted weight = 0.016 neff = 2018.10
config 54/64=[ 0.75 3.00] weight = 0.011 adjusted weight = 0.013 neff = 2066.85
config 55/64=[ -3.00 -0.75] weight = 0.009 adjusted weight = 0.010 neff = 2124.68
config 56/64=[ 2.25 2.25] weight = 0.009 adjusted weight = 0.010 neff = 2032.88
config 57/64=[ 2.25 -2.25] weight = 0.016 adjusted weight = 0.019 neff = 2042.42
config 58/64=[ 1.50 -3.00] weight = 0.005 adjusted weight = 0.007 neff = 2063.13
config 59/64=[ 3.00 1.50] weight = 0.004 adjusted weight = 0.004 neff = 2015.49
config 60/64=[ 1.50 3.00] weight = 0.006 adjusted weight = 0.007 neff = 2052.12
config 61/64=[ 2.25 -3.00] weight = 0.003 adjusted weight = 0.004 neff = 2050.86
config 62/64=[ 3.00 -1.50] weight = 0.010 adjusted weight = 0.012 neff = 2022.78
config 63/64=[ 3.00 -2.25] weight = 0.005 adjusted weight = 0.006 neff = 2029.58
Done.
Expected effective number of parameters: 2070.494(18.418), eqv.#replicates: 1.470
DIC:
Mean of Deviance................. 12253.7
Deviance at Mean................. 10220.4
Effective number of parameters... 2033.32
DIC.............................. 14287
Marginal likelihood: Integration -8365.796155 Gaussian-approx -8366.059737
Compute the marginal for each of the 2 hyperparameters
Interpolation method: Auto
Compute the marginal for theta[0] to theta[1] using numerical integration...
Compute the marginal for theta[0] to theta[1] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/results.files]
Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini]
Preparations : 0.097 seconds
Approx inference: 209.341 seconds [0.1|0.0|4.1|90.2|5.5]%
Output : 0.583 seconds
---------------------------------
Total : 210.021 seconds
breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
results2 <- data.frame(bymID=BYM_data$bymID, CD_GEOCODI=BYM_data$CD_GEOCODI, fit_SMR = model_bym_null$summary.fitted.values$mean, CI95_lower = model_bym_null$summary.fitted.values$`0.025quant`, CI95_upper=model_bym_null$summary.fitted.values$`0.975quant`)
CT_shp_gg_SMR_smth <- CT_shp_gg_SMR %>% left_join(results2, by=c("CD_GEOCODI")) %>% mutate(fit_cut=cut(fit_SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))
Column `CD_GEOCODI` joining character vector and factor, coercing into character vector
plot_fort_maps2(CT_shp_gg_SMR_smth, "fit_cut","BYM smoothed SMR", "Aggregate BYM smoothed SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")
set.seed(2014)
plot(1,1, type="n", xlim=c(550,650), ylim=c(0,10),
main= "Confidence intervals of the SMR",
xlab="County", ylab="Relative Risk", xaxt="n")
abline(h=1, lty=2)
for(i in 500:650){
if(!is.na(results2$fit_SMR[i])){
if(results2$CI95_lower[i]>1 ) {
sig.col <- brewer.pal(4, "Reds")[4]
col <- sig.col
lty <- 2
#text(i, SMR_data$CI95_upper[i]+.31,
#srt=90, col=sig.col, cex=.85)
} else {
col <- "black"
lty <- 1
}
lines(c(i,i), c(results2$CI95_lower[i],results2$CI95_upper[i]), col=col, lty=lty)
points(x=i, y=results2$fit_SMR[i], pch=18, col=col)
}
}
covariates <- read_csv("Census_data/census_covariates_Fortaleza_01_03_19.csv",
col_types = cols(Cod_setor = col_character()))
Calculate LII
covariates <- covariates %>% mutate(Total_no_HH_in_CT=replace(Total_no_HH_in_CT, is.na(Total_no_HH_in_CT), 0), Total_HH_inc_in_CT=replace(Total_HH_inc_in_CT, is.na(Total_HH_inc_in_CT), 0), Mean_HH_inc=replace(Mean_HH_inc, is.na(Mean_HH_inc), 0))
covariates$LII <- NA
for (i in 1:3044){
CT_Code <- CT_shp@data$CD_GEOCODI[i]
neighbors_codes <- CT_shp@data$CD_GEOCODI[CT_wm[[i]]]
total_nb_inc <- sum(covariates[(covariates$Cod_setor %in% neighbors_codes),]$Total_HH_inc_in_CT)
total_nb_hh <- sum(covariates[(covariates$Cod_setor %in% neighbors_codes),]$Total_no_HH_in_CT)
Mean_nb_inc <- total_nb_inc / total_nb_hh
LII <- Mean_nb_inc / covariates[(covariates$Cod_setor)==CT_Code,]$Mean_HH_inc
covariates[(covariates$Cod_setor==CT_Code),]$LII <- LII
}
covariates$LII[covariates$LII==Inf] <- NA
covariates$log_LII <- log(covariates$LII)
BYM_data_covar <- BYM_data %>% left_join(covariates, by=c("CD_GEOCODI"="Cod_setor")) %>% mutate(log_mean_HH_inc=log(Mean_HH_inc)) %>% arrange(CD_GEOCODI) %>% mutate(bymID=1:3044)
BYM_data_covar <- BYM_data_covar %>% mutate(log_mean_HH_inc=replace(log_mean_HH_inc, log_mean_HH_inc==-Inf | is.na(log_mean_HH_inc), 0), log_LII=replace(log_LII, log_LII==-Inf | is.na(log_LII), 0), Perc_Wtr_Spply_Ntwrk=replace(Perc_Wtr_Spply_Ntwrk, is.na(Perc_Wtr_Spply_Ntwrk), 0), Perc_branca=replace(Perc_branca, is.na(Perc_branca), 0), Perc_Garbage_Col_Serv=replace(Perc_Garbage_Col_Serv, is.na(Perc_Garbage_Col_Serv), 0), Perc_PPH_Elec=replace(Perc_PPH_Elec, is.na(Perc_PPH_Elec), 0), Lit_rate=replace(Lit_rate, is.na(Lit_rate), 0), ICE=replace(ICE, is.na(ICE), 0))
BYM_data_covar <- BYM_data_covar %>% mutate(ICE_quant=cut(ICE, breaks=quantile(BYM_data_covar$ICE, probs=c(seq(0,1,0.25),1)[1:5]), include.lowest=TRUE))
formula_bym_7 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + log_inc_quant + ICE_quant + log_LII_quant + Lit_rate_demean + Perc_branca_demean
model_bym_7 <- inla(formula_bym_7, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)
hgid: 29c6a7f1b1ff date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini] max_threads=[4]
inla_build...
number of sections=[19]
parse section=[0] name=[INLA.libR] type=[LIBR]
inla_parse_libR...
section[INLA.libR]
R_HOME=[/Library/Frameworks/R.framework/Resources]
parse section=[18] name=[INLA.Expert] type=[EXPERT]
inla_parse_expert...
section[INLA.Expert]
disable.gaussian.check=[0]
cpo.manual=[0]
jp.Rfile=[(null)]
jp.RData=NULL
jp.func=[(null)]
parse section=[1] name=[INLA.Model] type=[PROBLEM]
inla_parse_problem...
name=[INLA.Model]
openmp.strategy=[default]
store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/results.files]
output:
cpo=[0]
po=[0]
dic=[1]
kld=[1]
mlik=[1]
q=[0]
graph=[0]
gdensity=[0]
hyperparameters=[1]
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[3] name=[Predictor] type=[PREDICTOR]
inla_parse_predictor ...
section=[Predictor]
dir=[predictor]
PRIOR->name=[loggamma]
hyperid=[53001|Predictor]
PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR->PARAMETERS=[1, 1e-05]
initialise log_precision[12]
fixed=[1]
user.scale=[1]
n=[3044]
m=[0]
ndata=[3044]
compute=[1]
read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 19/3044 (idx,y) = (19, 0)
Aext=[(null)]
AextPrecision=[1e+08]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
parse section=[2] name=[INLA.Data1] type=[DATA]
inla_parse_data [section 1]...
tag=[INLA.Data1]
family=[POISSON]
likelihood=[POISSON]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f40eefc65]
file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f9fc6c31]
read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f40eefc65]
0/3044 (idx,a,y,d) = (0, 14.827, 12, 1)
1/3044 (idx,a,y,d) = (1, 4.88122, 4, 1)
2/3044 (idx,a,y,d) = (2, 9.75508, 31, 1)
3/3044 (idx,a,y,d) = (3, 10.764, 10, 1)
4/3044 (idx,a,y,d) = (4, 7.50958, 5, 1)
5/3044 (idx,a,y,d) = (5, 7.69529, 9, 1)
6/3044 (idx,a,y,d) = (6, 4.62971, 7, 1)
7/3044 (idx,a,y,d) = (7, 6.07998, 11, 1)
8/3044 (idx,a,y,d) = (8, 5.20853, 6, 1)
9/3044 (idx,a,y,d) = (9, 9.1703, 1, 1)
10/3044 (idx,a,y,d) = (10, 5.07622, 5, 1)
11/3044 (idx,a,y,d) = (11, 5.27241, 1, 1)
12/3044 (idx,a,y,d) = (12, 2.71774, 4, 1)
13/3044 (idx,a,y,d) = (13, 3.94485, 1, 1)
14/3044 (idx,a,y,d) = (14, 6.43779, 3, 1)
15/3044 (idx,a,y,d) = (15, 5.35615, 4, 1)
16/3044 (idx,a,y,d) = (16, 8.77675, 2, 1)
17/3044 (idx,a,y,d) = (17, 5.14462, 2, 1)
18/3044 (idx,a,y,d) = (18, 5.87517, 1, 1)
19/3044 (idx,a,y,d) = (19, 5.50689, 3, 1)
likelihood.variant=[0]
Link model [LOG]
Link order [-1]
Link variant [-1]
Link ntheta [0]
mix.use[0]
parse section=[16] name=[bymID] type=[FFIELD]
inla_parse_ffield...
section=[bymID]
dir=[random.effect00000001]
model=[bym]
PRIOR0->name=[loggamma]
hyperid=[10001|bymID]
PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR0->PARAMETERS0=[1, 0.0005]
PRIOR1->name=[loggamma]
hyperid=[10002|bymID]
PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
PRIOR1->PARAMETERS1=[1, 0.0005]
correct=[-1]
constr=[0]
diagonal=[1.01511e-05]
id.names=<not present>
compute=[1]
nrep=[1]
ngroup=[1]
read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 2/3044 (idx,y) = (2, 2)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 3/3044 (idx,y) = (3, 3)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 4/3044 (idx,y) = (4, 4)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 5/3044 (idx,y) = (5, 5)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 6/3044 (idx,y) = (6, 6)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 7/3044 (idx,y) = (7, 7)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 8/3044 (idx,y) = (8, 8)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 9/3044 (idx,y) = (9, 9)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 10/3044 (idx,y) = (10, 10)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 11/3044 (idx,y) = (11, 11)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 12/3044 (idx,y) = (12, 12)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 13/3044 (idx,y) = (13, 13)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 14/3044 (idx,y) = (14, 14)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 15/3044 (idx,y) = (15, 15)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 16/3044 (idx,y) = (16, 16)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 17/3044 (idx,y) = (17, 17)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 18/3044 (idx,y) = (18, 18)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 19/3044 (idx,y) = (19, 19)
read graph from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f20c0bc3d]
file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2a69cfc6]
nlocations=[3044]
locations[0]=[1]
locations[1]=[2]
locations[2]=[3]
locations[3]=[4]
locations[4]=[5]
locations[5]=[6]
locations[6]=[7]
locations[7]=[8]
locations[8]=[9]
locations[9]=[10]
locations[10]=[11]
locations[11]=[12]
locations[12]=[13]
locations[13]=[14]
locations[14]=[15]
locations[15]=[16]
locations[16]=[17]
locations[17]=[18]
locations[18]=[19]
locations[19]=[20]
initialise log_precision (iid component)[4]
fixed=[0]
initialise log_precision (spatial component)[4]
fixed=[0]
adjust.for.con.comp[1]
scale.model[0]
read extra constraint from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f71e05f37]
Constraint[0]
A[3044] = 1.000000
A[3045] = 1.000000
A[3046] = 1.000000
A[3047] = 1.000000
A[3048] = 1.000000
A[3049] = 1.000000
A[3050] = 1.000000
A[3051] = 1.000000
A[3052] = 1.000000
A[3053] = 1.000000
A[3054] = 1.000000
A[3055] = 1.000000
A[3056] = 1.000000
A[3057] = 1.000000
A[3058] = 1.000000
A[3059] = 1.000000
A[3060] = 1.000000
A[3061] = 1.000000
A[3062] = 1.000000
A[3063] = 1.000000
A[3064] = 1.000000
e[0] = 0.000000
rank-deficiency is *defined* [1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[4] name=[(Intercept)] type=[LINEAR]
inla_parse_linear...
section[(Intercept)]
dir=[fixed.effect00000001]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 0/3044 (idx,y) = (0, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 8/3044 (idx,y) = (8, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 10/3044 (idx,y) = (10, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 12/3044 (idx,y) = (12, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 14/3044 (idx,y) = (14, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 16/3044 (idx,y) = (16, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 17/3044 (idx,y) = (17, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 18/3044 (idx,y) = (18, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[5] name=[log_inc_quant(6.95,7.3] type=[LINEAR]
inla_parse_linear...
section[log_inc_quant(6.95,7.3]
dir=[fixed.effect00000002]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[6] name=[log_inc_quant(7.3,7.81] type=[LINEAR]
inla_parse_linear...
section[log_inc_quant(7.3,7.81]
dir=[fixed.effect00000003]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 8/3044 (idx,y) = (8, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 10/3044 (idx,y) = (10, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 12/3044 (idx,y) = (12, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 18/3044 (idx,y) = (18, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[7] name=[log_inc_quant(7.81,9.99] type=[LINEAR]
inla_parse_linear...
section[log_inc_quant(7.81,9.99]
dir=[fixed.effect00000004]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 14/3044 (idx,y) = (14, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 16/3044 (idx,y) = (16, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 17/3044 (idx,y) = (17, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[8] name=[ICE_quant(-0.185,-0.0955] type=[LINEAR]
inla_parse_linear...
section[ICE_quant(-0.185,-0.0955]
dir=[fixed.effect00000005]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 1/3044 (idx,y) = (1, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[9] name=[ICE_quant(-0.0955,-0.00566] type=[LINEAR]
inla_parse_linear...
section[ICE_quant(-0.0955,-0.00566]
dir=[fixed.effect00000006]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 8/3044 (idx,y) = (8, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 10/3044 (idx,y) = (10, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 12/3044 (idx,y) = (12, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 14/3044 (idx,y) = (14, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 16/3044 (idx,y) = (16, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 17/3044 (idx,y) = (17, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 18/3044 (idx,y) = (18, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[10] name=[ICE_quant(-0.00566,0.888] type=[LINEAR]
inla_parse_linear...
section[ICE_quant(-0.00566,0.888]
dir=[fixed.effect00000007]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[11] name=[log_LII_quant(-0.169,0.07] type=[LINEAR]
inla_parse_linear...
section[log_LII_quant(-0.169,0.07]
dir=[fixed.effect00000008]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 11/3044 (idx,y) = (11, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 13/3044 (idx,y) = (13, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 15/3044 (idx,y) = (15, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[12] name=[log_LII_quant(0.07,0.337] type=[LINEAR]
inla_parse_linear...
section[log_LII_quant(0.07,0.337]
dir=[fixed.effect00000009]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 0/3044 (idx,y) = (0, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 2/3044 (idx,y) = (2, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 3/3044 (idx,y) = (3, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 4/3044 (idx,y) = (4, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 5/3044 (idx,y) = (5, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 6/3044 (idx,y) = (6, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 7/3044 (idx,y) = (7, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 9/3044 (idx,y) = (9, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 19/3044 (idx,y) = (19, 1)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[13] name=[log_LII_quant(0.337,2.3] type=[LINEAR]
inla_parse_linear...
section[log_LII_quant(0.337,2.3]
dir=[fixed.effect00000010]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 0/3044 (idx,y) = (0, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 1/3044 (idx,y) = (1, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 2/3044 (idx,y) = (2, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 3/3044 (idx,y) = (3, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 4/3044 (idx,y) = (4, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 5/3044 (idx,y) = (5, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 6/3044 (idx,y) = (6, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 7/3044 (idx,y) = (7, 1)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 8/3044 (idx,y) = (8, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 9/3044 (idx,y) = (9, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 10/3044 (idx,y) = (10, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 11/3044 (idx,y) = (11, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 12/3044 (idx,y) = (12, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 13/3044 (idx,y) = (13, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 14/3044 (idx,y) = (14, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 15/3044 (idx,y) = (15, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 16/3044 (idx,y) = (16, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 17/3044 (idx,y) = (17, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 18/3044 (idx,y) = (18, 0)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 19/3044 (idx,y) = (19, 0)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[14] name=[Lit_rate_demean] type=[LINEAR]
inla_parse_linear...
section[Lit_rate_demean]
dir=[fixed.effect00000011]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 0/3044 (idx,y) = (0, -0.057515)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 1/3044 (idx,y) = (1, 0.0439105)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 2/3044 (idx,y) = (2, 0.00388049)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 3/3044 (idx,y) = (3, -0.00393435)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 4/3044 (idx,y) = (4, -0.0287495)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 5/3044 (idx,y) = (5, -0.00862934)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 6/3044 (idx,y) = (6, 0.0753386)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 7/3044 (idx,y) = (7, 0.0304397)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 8/3044 (idx,y) = (8, 0.0574549)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 9/3044 (idx,y) = (9, -0.00361096)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 10/3044 (idx,y) = (10, 0.0301058)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 11/3044 (idx,y) = (11, 0.0421761)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 12/3044 (idx,y) = (12, 0.0875771)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 13/3044 (idx,y) = (13, -0.00914456)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 14/3044 (idx,y) = (14, 0.0715713)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 15/3044 (idx,y) = (15, 0.0595273)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 16/3044 (idx,y) = (16, 0.0674131)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 17/3044 (idx,y) = (17, 0.0664691)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 18/3044 (idx,y) = (18, 0.0644035)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 19/3044 (idx,y) = (19, 0.0203868)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
section=[15] name=[Perc_branca_demean] type=[LINEAR]
inla_parse_linear...
section[Perc_branca_demean]
dir=[fixed.effect00000012]
file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d]
read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d]
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 0/3044 (idx,y) = (0, -0.129052)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 1/3044 (idx,y) = (1, 0.00306269)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 2/3044 (idx,y) = (2, 0.00328586)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 3/3044 (idx,y) = (3, -0.104188)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 4/3044 (idx,y) = (4, -0.0674784)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 5/3044 (idx,y) = (5, 0.056489)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 6/3044 (idx,y) = (6, -0.00537394)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 7/3044 (idx,y) = (7, 0.0141822)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 8/3044 (idx,y) = (8, 0.0526717)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 9/3044 (idx,y) = (9, -0.0683338)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 10/3044 (idx,y) = (10, 0.000844842)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 11/3044 (idx,y) = (11, 0.0363403)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 12/3044 (idx,y) = (12, 0.0843284)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 13/3044 (idx,y) = (13, 0.0119034)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 14/3044 (idx,y) = (14, 0.132056)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 15/3044 (idx,y) = (15, 0.0669073)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 16/3044 (idx,y) = (16, 0.061721)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 17/3044 (idx,y) = (17, 0.0317377)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 18/3044 (idx,y) = (18, 0.0831232)
file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 19/3044 (idx,y) = (19, -0.0500955)
prior mean=[0]
prior precision=[0.001]
compute=[1]
output:
summary=[1]
return.marginals=[1]
nquantiles=[3] [ 0.025 0.5 0.975 ]
ncdf=[0] [ ]
Index table: number of entries[14], total length[9144]
tag start-index length
Predictor 0 3044
bymID 3044 6088
(Intercept) 9132 1
log_inc_quant(6.95,7.3 9133 1
log_inc_quant(7.3,7.81 9134 1
log_inc_quant(7.81,9.99 9135 1
ICE_quant(-0.185,-0.0955 9136 1
ICE_quant(-0.0955,-0.00566 9137 1
ICE_quant(-0.00566,0.888 9138 1
log_LII_quant(-0.169,0.07 9139 1
log_LII_quant(0.07,0.337 9140 1
log_LII_quant(0.337,2.3 9141 1
Lit_rate_demean 9142 1
Perc_branca_demean 9143 1
parse section=[17] name=[INLA.Parameters] type=[INLA]
inla_parse_INLA...
section[INLA.Parameters]
lincomb.derived.only = [Yes]
lincomb.derived.correlation.matrix = [No]
global_node.factor = 2.000
global_node.degree = 2147483647
reordering = -1
Contents of ai_param 0x7fb389d0b8e0
Optimiser: DEFAULT METHOD
Option for domin-BFGS: epsx = 0.005
Option for domin-BFGS: epsf = 1e-05 (rounding error)
Option for domin-BFGS: epsg = 0.005
Option for GSL-BFGS2: tol = 0.1
Option for GSL-BFGS2: step_size = 1
Option for GSL-BFGS2: epsx = 0.005
Option for GSL-BFGS2: epsf = 0.000353553
Option for GSL-BFGS2: epsg = 0.005
Restart: 0
Mode known: No
Gaussian approximation:
abserr_func = 0.0005
abserr_step = 0.0005
optpar_fp = 0
optpar_nr_step_factor = -0.1
Gaussian data: No
Strategy: Use a mean-skew corrected Gaussian by fitting a Skew-Normal
Fast mode: On
Use linear approximation to log(|Q +c|)? Yes
Method: Compute the derivative exact
Parameters for improved approximations
Number of points evaluate: 9
Step length to compute derivatives numerically: 0.000100002
Stencil to compute derivatives numerically: 5
Cutoff value to construct local neigborhood: 0.0001
Log calculations: On
Log calculated marginal for the hyperparameters: On
Integration strategy: Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
f0 (CCD only): 1.100000
dz (GRID only): 0.750000
Adjust weights (GRID only): On
Difference in log-density limit (GRID only): 6.000000
Skip configurations with (presumed) small density (GRID only): On
Gradient is computed using Central difference with step-length 0.010000
Hessian is computed using Central difference with step-length 0.100000
Hessian matrix is forced to be a diagonal matrix? [No]
Compute effective number of parameters? [Yes]
Perform a Monte Carlo error-test? [No]
Interpolator [Auto]
CPO required diff in log-density [3]
Stupid search mode:
Status [On]
Max iter [1000]
Factor [1.05]
Numerical integration of hyperparameters:
Maximum number of function evaluations [100000]
Relative error ....................... [1e-05]
Absolute error ....................... [1e-06]
To stabilise the numerical optimisation:
Minimum value of the -Hessian [-inf]
CPO manual calculation[No]
Laplace-correction is Disabled.
inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini]
inla_INLA...
Strategy = [DEFAULT]
Size is [9144]
Chose OpenMP-strategy [LARGE]
Chose density-strategy [HIGH]
Size of graph=[9144] constraints=[1]
Found optimal reordering=[amdc] nnz(L)=[116632] and use_global_nodes(user)=[no]
List of hyperparameters:
theta[0] = [Log precision for bymID (idd component)]
theta[1] = [Log precision for bymID (spatial component)]
Optimise using DEFAULT METHOD
max.logdens= -11670.458086 fn= 1 theta= 3.990000 4.000000 range=[-1.922 3.256]
max.logdens= -10288.103692 fn= 5 theta= 3.017731 3.812525 range=[-2.095 4.093]
max.logdens= -10286.780733 fn= 6 theta= 3.017731 3.802525 range=[-2.095 4.093]
max.logdens= -10273.840958 fn= 8 theta= 3.007731 3.812525 range=[-2.097 4.099]
max.logdens= -8339.572897 fn= 10 theta= 1.023300 3.431870 range=[-2.321 5.106]
max.logdens= -8339.476174 fn= 11 theta= 1.023300 3.421870 range=[-2.320 5.106]
max.logdens= -8336.510453 fn= 13 theta= 1.013300 3.431870 range=[-2.322 5.108]
max.logdens= -8272.652350 fn= 16 theta= 0.528709 3.337473 range=[-2.391 5.186]
max.logdens= -8272.636538 fn= 17 theta= 0.528709 3.327473 range=[-2.391 5.186]
max.logdens= -8272.314532 fn= 19 theta= 0.538709 3.337473 range=[-2.390 5.185]
Iter=1 |grad|=37.1 |x-x.old|=2.5 |f-f.old|=3.41e+03
max.logdens= -8271.726058 fn= 21 theta= 0.720367 2.356011 range=[-2.311 5.164]
max.logdens= -8271.684499 fn= 22 theta= 0.720367 2.346011 range=[-2.310 5.164]
max.logdens= -8271.048353 fn= 23 theta= 0.710367 2.356011 range=[-2.312 5.165]
max.logdens= -8270.181173 fn= 26 theta= 0.637018 2.782835 range=[-2.347 5.174]
max.logdens= -8270.075973 fn= 27 theta= 0.637018 2.772835 range=[-2.347 5.174]
max.logdens= -8269.873145 fn= 29 theta= 0.627018 2.782835 range=[-2.349 5.175]
Iter=2 |grad|=20.5 |x-x.old|=0.358 |f-f.old|=2.54
max.logdens= -8266.203308 fn= 36 theta= 0.652074 1.840531 range=[-2.292 5.176]
max.logdens= -8266.105033 fn= 37 theta= 0.652074 1.830531 range=[-2.292 5.176]
max.logdens= -8266.029120 fn= 38 theta= 0.642074 1.840531 range=[-2.294 5.177]
max.logdens= -8265.501163 fn= 42 theta= 0.659774 1.547367 range=[-2.274 5.177]
max.logdens= -8265.347703 fn= 43 theta= 0.659774 1.537367 range=[-2.274 5.177]
max.logdens= -8265.219932 fn= 47 theta= 0.663684 1.398521 range=[-2.265 5.178]
max.logdens= -8265.211772 fn= 48 theta= 0.663684 1.388521 range=[-2.264 5.178]
max.logdens= -8265.208982 fn= 52 theta= 0.664443 1.369612 range=[-2.263 5.178]
Iter=3 |grad|=1.48 |x-x.old|=1.04 |f-f.old|=4.9
max.logdens= -8265.206218 fn= 59 theta= 0.667868 1.348524 range=[-2.261 5.178]
max.logdens= -8265.206095 fn= 64 theta= 0.668249 1.346177 range=[-2.261 5.178]
Iter=4 |grad|=0.339 |x-x.old|=0.0168 |f-f.old|=0.00289
max.logdens= -8265.206064 fn= 74 theta= 0.668249 1.346177 range=[-2.261 5.178]
max.logdens= -8265.206058 fn= 80 theta= 0.668249 1.346177 range=[-2.261 5.178]
Iter=5 |grad|=0.339 |x-x.old|=1.79e-08(pass) |f-f.old|=3.54e-05(pass) Reached numerical limit!
Number of function evaluations = 90
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]
603.265000 50.522614
50.522614 12.868753
Eigenvectors of the Hessian
0.996411 -0.084651
0.084651 0.996411
Eigenvalues of the Hessian
607.557221
8.576532
StDev/Correlation matrix (scaled inverse Hessian)
0.049696 -0.573408
0.340255
Compute corrected stdev for theta[0]: negative 0.985176 positive 0.998673
Compute corrected stdev for theta[1]: negative 0.809632 positive 1.132727
max.logdens= -8265.206087 fn= 104 theta= 0.668249 1.346177 range=[-2.261 5.178]
config 0=[ 0.00 0.00] log(rel.dens)=-0.12, [3] accept, compute, 10.16s
config 1=[ 0.00 -0.75] log(rel.dens)=-0.43, [2] accept, compute, 10.19s
config 2=[ -0.75 0.00] log(rel.dens)=-0.36, [1] accept, compute, 10.25s
config 3=[ 0.75 0.00] log(rel.dens)=-0.29, [0] accept, compute, 10.52s
config 4=[ -0.75 0.75] log(rel.dens)=-0.65, [2] accept, compute, 10.44s
config 5=[ 0.00 0.75] log(rel.dens)=-0.25, [3] accept, compute, 10.66s
config 6=[ -0.75 -0.75] log(rel.dens)=-0.66, [1] accept, compute, 10.64s
config 7=[ 0.75 -0.75] log(rel.dens)=-0.59, [0] accept, compute, 10.82s
config 8=[ 0.75 0.75] log(rel.dens)=-0.51, [2] accept, compute, 10.23s
config 9=[ 0.00 -1.50] log(rel.dens)=-1.64, [3] accept, compute, 10.19s
config 10=[ -1.50 0.00] log(rel.dens)=-1.14, [1] accept, compute, 10.23s
config 11=[ 1.50 0.00] log(rel.dens)=-1.11, [0] accept, compute, 10.23s
config 12=[ 0.00 1.50] log(rel.dens)=-0.91, [2] accept, compute, 9.97s
config 13=[ -0.75 1.50] log(rel.dens)=-1.57, [3] accept, compute, 10.07s
config 14=[ 0.75 -1.50] log(rel.dens)=-1.75, [1] accept, compute, 10.06s
config 15=[ -0.75 -1.50] log(rel.dens)=-2.10, [0] accept, compute, 10.26s
config 16=[ 0.75 1.50] log(rel.dens)=-1.01, [2] accept, compute, 10.13s
config 17=[ -1.50 -0.75] log(rel.dens)=-1.58, [3] accept, compute, 10.42s
config 18=[ 1.50 -0.75] log(rel.dens)=-1.37, [1] accept, compute, 10.33s
config 19=[ -1.50 0.75] log(rel.dens)=-1.62, [0] accept, compute, 10.37s
config 20=[ 1.50 0.75] log(rel.dens)=-1.28, [2] accept, compute, 10.32s
config 21=[ 1.50 1.50] log(rel.dens)=-1.80, [1] accept, compute, 10.21s
config 22=[ -1.50 -1.50] log(rel.dens)=-2.84, [3] accept, compute, 10.23s
config 23=[ 1.50 -1.50] log(rel.dens)=-2.50, [0] accept, compute, 10.23s
config 24=[ -1.50 1.50] log(rel.dens)=-2.61, [2] accept, compute, 9.96s
config 25=[ 0.00 -2.25] log(rel.dens)=-3.88, [1] accept, compute, 10.17s
config 26=[ 2.25 0.00] log(rel.dens)=-2.45, [3] accept, compute, 10.17s
config 27=[ -2.25 0.00] log(rel.dens)=-2.79, [0] accept, compute, 10.05s
config 28=[ 0.00 2.25] log(rel.dens)=-1.87, [2] accept, compute, 10.19s
config 29=[ -0.75 -2.25] log(rel.dens)=-4.47, [3] accept, compute, 10.20s
config 30=[ 2.25 0.75] log(rel.dens)=-2.61, [1] accept, compute, 10.27s
config 31=[ 0.75 -2.25] log(rel.dens)=-4.00, [0] accept, compute, 10.19s
config 32=[ -2.25 -0.75] log(rel.dens)=-2.83, [2] accept, compute, 10.49s
config 33=[ 2.25 -0.75] log(rel.dens)=-2.62, [3] accept, compute, 10.32s
config 34=[ -0.75 2.25] log(rel.dens)=-2.74, [1] accept, compute, 10.40s
config 35=[ -2.25 0.75] log(rel.dens)=-2.96, [0] accept, compute, 10.51s
config 36=[ 0.75 2.25] log(rel.dens)=-1.77, [2] accept, compute, 10.71s
config 37=[ -2.25 -1.50] log(rel.dens)=-4.23, [3] accept, compute, 10.70s
config 38=[ 2.25 -1.50] log(rel.dens)=-3.35, [1] accept, compute, 10.82s
config 39=[ -1.50 -2.25] log(rel.dens)=-5.54, [0] accept, compute, 10.76s
config 40=[ 2.25 1.50] log(rel.dens)=-3.04, [2] accept, compute, 11.06s
config 41=[ 1.50 -2.25] log(rel.dens)=-4.17, [1] accept, compute, 11.23s
config 42=[ -1.50 2.25] log(rel.dens)=-3.70, [3] accept, compute, 11.63s
config 43=[ -2.25 1.50] log(rel.dens)=-4.02, [0] accept, compute, 11.21s
config 44=[ 0.00 -3.00] log(rel.dens)=-7.93, reject, 0.27s
config 45=[ 1.50 2.25] log(rel.dens)=-2.33, [2] accept, compute, 10.14s
config 46=[ 0.00 3.00] log(rel.dens)=-2.98, [1] accept, compute, 10.24s
config 47=[ 3.00 0.00] log(rel.dens)=-4.37, [3] accept, compute, 10.10s
config 48=[ -3.00 0.00] log(rel.dens)=-4.43, [0] accept, compute, 10.23s
config 49=[ -3.00 0.75] log(rel.dens)=-5.00, [2] accept, compute, 10.20s
config 50=[ 3.00 0.75] log(rel.dens)=-4.87, [1] accept, compute, 10.20s
config 51=[ -0.75 3.00] log(rel.dens)=-3.85, [3] accept, compute, 10.32s
config 52=[ 0.75 3.00] log(rel.dens)=-2.71, [0] accept, compute, 10.18s
config 53=[ 3.00 -0.75] log(rel.dens)=-4.44, [2] accept, compute, 10.36s
config 54=[ -2.25 -2.25] log(rel.dens)=-7.09, reject, 0.28s
config 55=[ -3.00 -0.75] log(rel.dens)=-4.72, [1] accept, compute, 10.29s
config 56=[ 2.25 2.25] log(rel.dens)=-3.66, [3] accept, compute, 10.30s
config 57=[ -3.00 -1.50] log(rel.dens)=-6.15, reject, 0.26s
config 58=[ 2.25 -2.25] log(rel.dens)=-4.97, [0] accept, compute, 10.45s
config 59=[ -2.25 2.25] log(rel.dens)=-5.52, [2] accept, compute, 10.53s
config 60=[ -3.00 1.50] log(rel.dens)=-6.22, reject, 0.21s
config 61=[ -1.50 3.00] log(rel.dens)=-5.31, [1] accept, compute, 10.54s
config 62=[ 3.00 -2.25] log(rel.dens)=-6.28, reject, 0.30s
config 63=[ 3.00 1.50] log(rel.dens)=-4.83, [3] accept, compute, 10.51s
config 64=[ 1.50 3.00] log(rel.dens)=-3.04, [0] accept, compute, 10.39s
config 65=[ 3.00 -1.50] log(rel.dens)=-4.98, [2] accept, compute, 10.29s
config 66=[ -2.25 3.00] log(rel.dens)=-7.37, reject, 0.28s
config 67=[ 3.75 0.00] log(rel.dens)=-6.84, reject, 0.30s
config 68=[ 2.25 3.00] log(rel.dens)=-4.03, [3] accept, compute, 10.21s
config 69=[ -3.75 0.00] log(rel.dens)=-6.90, reject, 0.30s
config 70=[ 3.00 2.25] log(rel.dens)=-5.17, [1] accept, compute, 10.57s
config 71=[ 0.00 3.75] log(rel.dens)=-4.39, [0] accept, compute, 10.19s
config 72=[ -1.50 3.75] log(rel.dens)=-7.18, reject, 0.27s
config 73=[ -0.75 3.75] log(rel.dens)=-5.69, [3] accept, compute, 11.03s
config 74=[ 0.75 3.75] log(rel.dens)=-3.78, [2] accept, compute, 11.00s
config 75=[ 1.50 3.75] log(rel.dens)=-3.91, [0] accept, compute, 11.03s
config 76=[ -0.75 4.50] log(rel.dens)=-7.38, reject, 0.20s
config 77=[ 3.00 3.00] log(rel.dens)=-5.51, [1] accept, compute, 12.15s
config 78=[ 2.25 3.75] log(rel.dens)=-4.74, [3] accept, compute, 10.29s
config 79=[ 0.00 4.50] log(rel.dens)=-5.83, [2] accept, compute, 10.57s
config 80=[ 0.75 4.50] log(rel.dens)=-5.03, [0] accept, compute, 10.67s
config 81=[ 0.00 5.25] log(rel.dens)=-7.45, reject, 0.20s
config 82=[ 3.00 4.50] log(rel.dens)=-6.45, reject, 0.20s
config 83=[ 1.50 4.50] log(rel.dens)=-4.89, [1] accept, compute, 10.26s
config 84=[ 3.00 3.75] log(rel.dens)=-5.86, [3] accept, compute, 6.37s
config 85=[ 2.25 4.50] log(rel.dens)=-5.28, [2] accept, compute, 6.11s
Combine the densities with relative weights:
config 0/74=[ 0.00 0.00] weight = 1.000 adjusted weight = 0.948 neff = 2011.50
config 1/74=[ 0.00 -0.75] weight = 0.735 adjusted weight = 0.706 neff = 2012.22
config 2/74=[ -0.75 0.00] weight = 0.784 adjusted weight = 0.753 neff = 2025.49
config 3/74=[ 0.75 0.00] weight = 0.839 adjusted weight = 0.805 neff = 1997.28
config 4/74=[ -0.75 0.75] weight = 0.590 adjusted weight = 0.574 neff = 2027.31
config 5/74=[ 0.00 0.75] weight = 0.876 adjusted weight = 0.841 neff = 2013.03
config 6/74=[ -0.75 -0.75] weight = 0.585 adjusted weight = 0.568 neff = 2025.91
config 7/74=[ 0.75 -0.75] weight = 0.627 adjusted weight = 0.609 neff = 1998.32
config 8/74=[ 0.75 0.75] weight = 0.679 adjusted weight = 0.661 neff = 1998.71
config 9/74=[ 0.00 -1.50] weight = 0.218 adjusted weight = 0.218 neff = 2015.95
config 10/74=[ -1.50 0.00] weight = 0.359 adjusted weight = 0.358 neff = 2039.36
config 11/74=[ 1.50 0.00] weight = 0.372 adjusted weight = 0.371 neff = 1983.06
config 12/74=[ 0.00 1.50] weight = 0.452 adjusted weight = 0.451 neff = 2016.59
config 13/74=[ -0.75 1.50] weight = 0.235 adjusted weight = 0.237 neff = 2031.15
config 14/74=[ 0.75 -1.50] weight = 0.195 adjusted weight = 0.197 neff = 2002.47
config 15/74=[ -0.75 -1.50] weight = 0.138 adjusted weight = 0.140 neff = 2029.38
config 16/74=[ 0.75 1.50] weight = 0.411 adjusted weight = 0.415 neff = 2002.08
config 17/74=[ -1.50 -0.75] weight = 0.231 adjusted weight = 0.234 neff = 2039.66
config 18/74=[ 1.50 -0.75] weight = 0.287 adjusted weight = 0.290 neff = 1984.41
config 19/74=[ -1.50 0.75] weight = 0.223 adjusted weight = 0.225 neff = 2041.49
config 20/74=[ 1.50 0.75] weight = 0.314 adjusted weight = 0.317 neff = 1984.24
config 21/74=[ 1.50 1.50] weight = 0.185 adjusted weight = 0.195 neff = 1987.57
config 22/74=[ -1.50 -1.50] weight = 0.066 adjusted weight = 0.069 neff = 2042.54
config 23/74=[ 1.50 -1.50] weight = 0.093 adjusted weight = 0.097 neff = 1989.05
config 24/74=[ -1.50 1.50] weight = 0.083 adjusted weight = 0.087 neff = 2045.39
config 25/74=[ 0.00 -2.25] weight = 0.023 adjusted weight = 0.025 neff = 2023.02
config 26/74=[ 2.25 0.00] weight = 0.097 adjusted weight = 0.103 neff = 1968.71
config 27/74=[ -2.25 0.00] weight = 0.069 adjusted weight = 0.073 neff = 2053.40
config 28/74=[ 0.00 2.25] weight = 0.174 adjusted weight = 0.185 neff = 2021.70
config 29/74=[ -0.75 -2.25] weight = 0.013 adjusted weight = 0.014 neff = 2035.95
config 30/74=[ 2.25 0.75] weight = 0.083 adjusted weight = 0.089 neff = 1969.67
config 31/74=[ 0.75 -2.25] weight = 0.021 adjusted weight = 0.022 neff = 2010.22
config 32/74=[ -2.25 -0.75] weight = 0.066 adjusted weight = 0.071 neff = 2053.12
config 33/74=[ 2.25 -0.75] weight = 0.082 adjusted weight = 0.088 neff = 1970.37
config 34/74=[ -0.75 2.25] weight = 0.073 adjusted weight = 0.078 neff = 2036.36
config 35/74=[ -2.25 0.75] weight = 0.058 adjusted weight = 0.063 neff = 2055.38
config 36/74=[ 0.75 2.25] weight = 0.192 adjusted weight = 0.207 neff = 2007.07
config 37/74=[ -2.25 -1.50] weight = 0.016 adjusted weight = 0.018 neff = 2055.76
config 38/74=[ 2.25 -1.50] weight = 0.039 adjusted weight = 0.044 neff = 1975.21
config 39/74=[ -1.50 -2.25] weight = 0.004 adjusted weight = 0.005 neff = 2048.82
config 40/74=[ 2.25 1.50] weight = 0.054 adjusted weight = 0.060 neff = 1972.80
config 41/74=[ 1.50 -2.25] weight = 0.017 adjusted weight = 0.019 neff = 1997.00
config 42/74=[ -1.50 2.25] weight = 0.028 adjusted weight = 0.031 neff = 2050.49
config 43/74=[ -2.25 1.50] weight = 0.020 adjusted weight = 0.023 neff = 2059.35
config 44/74=[ 1.50 2.25] weight = 0.109 adjusted weight = 0.122 neff = 1992.37
config 45/74=[ 0.00 3.00] weight = 0.057 adjusted weight = 0.066 neff = 2027.97
config 46/74=[ 3.00 0.00] weight = 0.014 adjusted weight = 0.016 neff = 1954.30
config 47/74=[ -3.00 0.00] weight = 0.013 adjusted weight = 0.016 neff = 2066.88
config 48/74=[ -3.00 0.75] weight = 0.008 adjusted weight = 0.009 neff = 2069.28
config 49/74=[ 3.00 0.75] weight = 0.009 adjusted weight = 0.010 neff = 1955.30
config 50/74=[ -0.75 3.00] weight = 0.024 adjusted weight = 0.028 neff = 2042.50
config 51/74=[ 0.75 3.00] weight = 0.075 adjusted weight = 0.088 neff = 2013.31
config 52/74=[ 3.00 -0.75] weight = 0.013 adjusted weight = 0.015 neff = 1956.28
config 53/74=[ -3.00 -0.75] weight = 0.010 adjusted weight = 0.012 neff = 2066.59
config 54/74=[ 2.25 2.25] weight = 0.029 adjusted weight = 0.034 neff = 1977.70
config 55/74=[ 2.25 -2.25] weight = 0.008 adjusted weight = 0.009 neff = 1983.84
config 56/74=[ -2.25 2.25] weight = 0.005 adjusted weight = 0.005 neff = 2064.71
config 57/74=[ -1.50 3.00] weight = 0.006 adjusted weight = 0.007 neff = 2056.89
config 58/74=[ 3.00 1.50] weight = 0.009 adjusted weight = 0.011 neff = 1957.91
config 59/74=[ 1.50 3.00] weight = 0.054 adjusted weight = 0.066 neff = 1998.53
config 60/74=[ 3.00 -1.50] weight = 0.008 adjusted weight = 0.009 neff = 1961.53
config 61/74=[ 2.25 3.00] weight = 0.020 adjusted weight = 0.026 neff = 1983.67
config 62/74=[ 3.00 2.25] weight = 0.006 adjusted weight = 0.008 neff = 1962.55
config 63/74=[ 0.00 3.75] weight = 0.014 adjusted weight = 0.018 neff = 2035.28
config 64/74=[ -0.75 3.75] weight = 0.004 adjusted weight = 0.005 neff = 2049.96
config 65/74=[ 0.75 3.75] weight = 0.026 adjusted weight = 0.033 neff = 2020.53
config 66/74=[ 1.50 3.75] weight = 0.023 adjusted weight = 0.031 neff = 2005.76
config 67/74=[ 3.00 3.00] weight = 0.005 adjusted weight = 0.006 neff = 1968.58
config 68/74=[ 2.25 3.75] weight = 0.010 adjusted weight = 0.014 neff = 1990.94
config 69/74=[ 0.00 4.50] weight = 0.003 adjusted weight = 0.005 neff = 2043.20
config 70/74=[ 0.75 4.50] weight = 0.007 adjusted weight = 0.011 neff = 2028.54
config 71/74=[ 1.50 4.50] weight = 0.008 adjusted weight = 0.013 neff = 2013.79
config 72/74=[ 3.00 3.75] weight = 0.003 adjusted weight = 0.005 neff = 1975.71
config 73/74=[ 2.25 4.50] weight = 0.006 adjusted weight = 0.009 neff = 1998.83
Done.
Expected effective number of parameters: 2011.203(19.240), eqv.#replicates: 1.514
DIC:
Mean of Deviance................. 12183.6
Deviance at Mean................. 10209.6
Effective number of parameters... 1973.98
DIC.............................. 14157.6
Marginal likelihood: Integration -8267.263924 Gaussian-approx -8267.647448
Compute the marginal for each of the 2 hyperparameters
Interpolation method: Auto
Compute the marginal for theta[0] to theta[1] using numerical integration...
Compute the marginal for theta[0] to theta[1] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/results.files]
Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini]
Preparations : 0.152 seconds
Approx inference: 216.252 seconds [0.2|0.0|3.8|89.9|6.1]%
Output : 0.951 seconds
---------------------------------
Total : 217.356 seconds
formula_bym_8 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + Perc_Wtr_Spply_Ntwrk + Perc_Garbage_Col_Serv + Perc_PPH_Elec + Lit_rate + log_mean_HH_inc + ICE + log_LII + Perc_branca
model_bym_8 <- inla(formula_bym_8, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), verbose = TRUE)
formula_bym_9 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + Perc_Garbage_Col_Serv + Lit_rate + log_mean_HH_inc + ICE_quant + Perc_branca
model_bym_9 <- inla(formula_bym_9, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), verbose = TRUE)
summary(model_bym_1)
Call:
c("inla(formula = formula_bym_1, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.5329 199.1192 1.2199 201.8720
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 4.2557 0.2553 3.7528 4.2563 4.7551 4.2574 0
log_mean_HH_inc -0.6256 0.0344 -0.6929 -0.6256 -0.5580 -0.6258 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.958 0.094 1.776 1.957 2.146 1.958
Precision for bymID (spatial component) 3.818 1.177 2.112 3.612 6.675 3.236
Expected number of effective parameters(std dev): 2010.94(19.19)
Number of equivalent replicates : 1.514
Marginal log-Likelihood: -8222.09
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_2)
Call:
c("inla(formula = formula_bym_2, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.7008 243.0247 1.4088 246.1342
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) -0.0146 0.0343 -0.0821 -0.0146 0.0525 -0.0145 0
ICE_quant(-0.185,-0.0955 -0.2265 0.0454 -0.3156 -0.2265 -0.1376 -0.2265 0
ICE_quant(-0.0955,-0.00566 -0.4662 0.0479 -0.5604 -0.4662 -0.3722 -0.4662 0
ICE_quant(-0.00566,0.888 -0.9566 0.0644 -1.0832 -0.9566 -0.8304 -0.9565 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.986 0.097 1.799 1.985 2.180 1.984
Precision for bymID (spatial component) 2.468 0.601 1.546 2.378 3.886 2.203
Expected number of effective parameters(std dev): 2029.78(18.92)
Number of equivalent replicates : 1.50
Marginal log-Likelihood: -8270.07
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_3)
Call:
c("inla(formula = formula_bym_3, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.3041 176.7624 0.6840 178.7505
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) -0.4699 0.0173 -0.5040 -0.4698 -0.4362 -0.4697 0
log_LII 0.5143 0.0373 0.4411 0.5142 0.5876 0.5141 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 2.379 0.1424 2.1090 2.376 2.670 2.3701
Precision for bymID (spatial component) 1.033 0.1444 0.7801 1.022 1.349 0.9989
Expected number of effective parameters(std dev): 2028.34(18.82)
Number of equivalent replicates : 1.501
Marginal log-Likelihood: -8279.68
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_4)
Call:
c("inla(formula = formula_bym_4, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.4813 328.0995 1.7753 331.3560
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 1.4307 0.5091 0.4261 1.4323 2.4254 1.4356 0
log_mean_HH_inc -0.2626 0.0662 -0.3919 -0.2628 -0.1322 -0.2632 0
ICE -1.5269 0.2366 -1.9932 -1.5264 -1.0641 -1.5253 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.940 0.0892 1.779 1.935 2.129 1.919
Precision for bymID (spatial component) 4.816 1.6323 2.332 4.583 8.664 4.141
Expected number of effective parameters(std dev): 2002.23(19.17)
Number of equivalent replicates : 1.52
Marginal log-Likelihood: -8206.72
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_5)
Call:
c("inla(formula = formula_bym_5, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.7538 351.4770 1.9814 355.2122
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 1.9154 0.5465 0.8356 1.9177 2.9820 1.9222 0
log_mean_HH_inc -0.3267 0.0712 -0.4657 -0.3270 -0.1862 -0.3275 0
ICE -1.6101 0.2376 -2.0778 -1.6097 -1.1448 -1.6089 0
log_LII -0.1266 0.0563 -0.2367 -0.1268 -0.0156 -0.1272 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.930 0.0851 1.768 1.927 2.103 1.922
Precision for bymID (spatial component) 5.569 2.0092 2.693 5.217 10.462 4.590
Expected number of effective parameters(std dev): 2001.86(19.23)
Number of equivalent replicates : 1.521
Marginal log-Likelihood: -8210.57
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_6)
Call:
c("inla(formula = formula_bym_6, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.5947 217.9480 0.6745 220.2172
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 0.5034 0.0648 0.3761 0.5034 0.6305 0.5034 0
Perc_branca -2.4497 0.1701 -2.7843 -2.4496 -2.1165 -2.4492 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.996 0.0992 1.805 1.994 2.195 1.992
Precision for bymID (spatial component) 2.266 0.5237 1.449 2.193 3.489 2.048
Expected number of effective parameters(std dev): 2033.13(18.77)
Number of equivalent replicates : 1.497
Marginal log-Likelihood: -8269.96
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_7)
Call:
c("inla(formula = formula_bym_7, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.4709 216.1419 1.1469 218.7597
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 3.5010 0.5374 2.4364 3.5042 4.5475 3.5105 0
Perc_Wtr_Spply_Ntwrk 0.3220 0.1812 -0.0329 0.3216 0.6784 0.3210 0
Perc_Garbage_Col_Serv 0.1436 0.0958 -0.0440 0.1435 0.3320 0.1431 0
Perc_PPH_Elec -0.3663 0.5553 -1.4455 -0.3702 0.7339 -0.3780 0
Lit_rate -4.6523 0.3011 -5.2440 -4.6521 -4.0620 -4.6518 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 2.089 0.1071 1.884 2.087 2.305 2.085
Precision for bymID (spatial component) 1.959 0.4061 1.302 1.910 2.887 1.812
Expected number of effective parameters(std dev): 2023.18(19.17)
Number of equivalent replicates : 1.505
Marginal log-Likelihood: -8266.42
Posterior marginals for linear predictor and fitted values computed
summary(model_bym_8)
Call:
c("inla(formula = formula_bym_8, family = \"poisson\", data = BYM_data_covar, ", " E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )
Time used:
Pre-processing Running inla Post-processing Total
1.6956 467.6865 1.1383 470.5205
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 2.5729 0.6673 1.2505 2.5770 3.8717 2.5851 0
Perc_Wtr_Spply_Ntwrk 0.0292 0.1769 -0.3173 0.0288 0.3771 0.0282 0
Perc_Garbage_Col_Serv 0.1834 0.0946 -0.0019 0.1832 0.3695 0.1829 0
Perc_PPH_Elec -0.1044 0.5703 -1.2202 -0.1059 1.0182 -0.1087 0
Lit_rate -1.8621 0.3805 -2.6091 -1.8622 -1.1156 -1.8622 0
log_mean_HH_inc -0.1743 0.0809 -0.3326 -0.1744 -0.0152 -0.1747 0
ICE -1.3500 0.2513 -1.8443 -1.3497 -0.8578 -1.3491 0
log_LII -0.1587 0.0550 -0.2664 -0.1588 -0.0505 -0.1590 0
Perc_branca -0.7198 0.2177 -1.1474 -0.7197 -0.2928 -0.7196 0
Random effects:
Name Model
bymID BYM model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for bymID (iid component) 1.916 0.0811 1.762 1.915 2.081 1.911
Precision for bymID (spatial component) 7.946 3.4837 3.320 7.232 16.670 6.040
Expected number of effective parameters(std dev): 1996.81(19.21)
Number of equivalent replicates : 1.524
Marginal log-Likelihood: -8214.82
Posterior marginals for linear predictor and fitted values computed
BYM_data_ICE <- BYM_data_covar %>% mutate(raw_SMR = y / E) %>% mutate(log_SMR = log(raw_SMR))
ggplot(BYM_data_ICE, aes(x=ICE_quant, y=raw_SMR)) + geom_boxplot() +
coord_cartesian(ylim = c(0, 10)) + geom_hline(yintercept = 1.0)
ggplot(BYM_data_ICE, aes(x=ICE_quant, y=log_SMR)) + geom_boxplot() + geom_hline(yintercept = 0.0)
BYM_data_ICE <- BYM_data_ICE %>% group_by(ICE_quant) %>% summarize(mean_SMR = mean(raw_SMR, na.rm=TRUE))
ggplot(BYM_data_ICE, aes(x=ICE_quant, y=mean_SMR)) + geom_bar(stat = "identity", fill="firebrick3") + geom_hline(yintercept = 1.0)
BYM_data_inc <- BYM_data_covar %>% mutate(raw_SMR = y / E) %>% mutate(log_SMR = log(raw_SMR))
ggplot(BYM_data_inc, aes(x=log_inc_quant, y=raw_SMR)) + geom_boxplot() +
coord_cartesian(ylim = c(0, 10)) + geom_hline(yintercept = 1.0)